Das virtuelle, optische Messen wird in der industriellen Anwendung häufig vernachlässigt. Um optische Messergebnisse jedoch vorhersehbar und zuverlässig zu machen, ist es erforderlich, Sensoren zu modellieren und die Resultate, sogenannte virtuelle Messergebnisse, zu analysieren. Die zulässigen Modellvereinfachungen sind dabei vom zugrunde liegenden, physikalischen Messprinzip abhängig. In dieser Arbeit werden zwei virtuelle, optische Sensoren mit unterschiedlichen Messprinzipien unter paraxialen Annahmen modelliert. Zudem werden Untersuchungen zum Übertragungsverhalten der Sensoren angestellt. Beim ersten Sensor handelt es sich um einen winkelauflösenden Streulichtsensor zur Messung der statistischen Verteilung von Gradienten geometrischer Oberflächen. Der zweite Sensor ist ein kurzkohärentes Interferometer zur vertikal hochauflösenden Messung von Topographien. Während dem winkelauflösenden Messprinzip ein inkohärenter Modellansatz zugrunde liegt, werden beim Interferometer kohärente Annahmen getroffen. Mithilfe der Sensormodelle ist es möglich, geometrische Oberflächen virtuell anzutasten und, basierend auf generierten oder real gemessenen Topographiedaten, virtuelle Messungen anzustellen. Auf diese Weise werden umfangreiche Untersuchungen zum Übertragungsverhalten der Sensoren ermöglicht. Darüber hinaus wird ein eigens entwickeltes, VTK-basiertes Programm vorgestellt, das die nichtsequentielle Berechnung optischer Sensoren ermöglicht. Dieses Programm nutzt Ray Tracing zur Simulation nichtsequentieller, optischer Systeme. Des Weiteren werden Ansätze für die parallele Datenverarbeitung mit CUDA® vorgestellt. Der paraxial modellierte, winkelauflösende Streulichtsensor wird demnach zusätzlich nichtsequentiell simuliert und die Ergebnisse der paraxialen und der nichtsequentiellen Berechnung werden gegenübergestellt.

Optical Character Recognition (OCR) system plays an important role in digitization of data acquired as images from a variety of sources. Although the area is very well explored for Latin languages, some of the languages based on Arabic cursive script are not yet explored. It is due to many factors: Most importantly are the unavailability of proper data sets and complexities posed by cursive scripts. The Pashto language is one of such languages which needs considerable exploration towards OCR. In order to develop such an OCR system, this thesis provides a pioneering study that explores deep learning for the Pashto language in the field of OCR. The Pashto language is spoken by more than $50$ million people across the world, and it is an active medium both for oral as well as written communication. It is associated with rich literary heritage and contains huge written collection. These written materials present contents of simple to complex nature, and layouts from hand-scribed to printed text. The Pashto language presents mainly two types of complexities (i) generic w.r.t. cursive script, (ii) specific w.r.t. Pashto language. Generic complexities are cursiveness, context dependency, and breaker character anomalies, as well as space anomalies. Pashto specific complexities are variations in shape for a single character and shape similarity for some of the additional Pashto characters. Existing research in the area of Arabic OCR did not lead to an end-to-end solution for the mentioned complexities and therefore could not be generalized to build a sophisticated OCR system for Pashto. The contribution of this thesis spans in three levels, conceptual level, data level, and practical level. In the conceptual level, we have deeply explored the Pashto language and identified those characters, which are responsible for the challenges mentioned above. In the data level, a comprehensive dataset is introduced containing real images of hand-scribed contents. The dataset is manually transcribed and has the most frequent layout patterns associated with the Pashto language. The practical level contribution provides a bridge, in the form of a complete Pashto OCR system, and connects the outcomes of the conceptual and data levels contributions. The practical contribution comprises of skew detection, text-line segmentation, feature extraction, classification, and post-processing. The OCR module is more strengthened by using deep learning paradigm to recognize Pashto cursive script by the framework of Recursive Neural Networks (RNN). Proposed Pashto text recognition is based on Long Short-Term Memory Network (LSTM) and realizes a character recognition rate of $90.78\%$ on Pashto real hand-scribed images. All these contributions are integrated into an application to provide a flexible and generic End-to-End Pashto OCR system. The impact of this thesis is not only specific to the Pashto language, but it is also beneficial to other cursive languages like Arabic, Urdu, and Persian e.t.c. The main reason is the Pashto character set, which is a superset of Arabic, Persian, and Urdu languages. Therefore, the conceptual contribution of this thesis provides insight and proposes solutions to almost all generic complexities associated with Arabic, Persian, and Urdu languages. For example, an anomaly caused by breaker characters is deeply analyzed, which is shared among 70 languages, mainly use Arabic script. This thesis presents a solution to this issue and is equally beneficial to almost all Arabic like languages. The scope of this thesis has two important aspects. First, a social impact, i.e., how a society may benefit from it. The main advantages are to bring the historical and almost vanished document to life and to ensure the opportunities to explore, analyze, translate, share, and understand the contents of Pashto language globally. Second, the advancement and exploration of the technical aspects. Because, this thesis empirically explores the recognition and challenges which are solely related to the Pashto language, both regarding character-set and the materials which present such complexities. Furthermore, the conceptual and practical background of this thesis regarding complexities of Pashto language is very beneficial regarding OCR for other cursive languages.

Nowadays, the increasing demand for ever more customizable products has emphasized the need for more flexible and fast-changing manufacturing systems. In this environment, simulation has become a strategic tool for the design, development, and implementation of such systems. Simulation represents a relatively low-cost and risk-free alternative for testing the impact and effectiveness of changes in different aspects of manufacturing systems. Systems that deal with this kind of data for its use in decision making processes are known as Simulation-Based Decision Support Systems (SB-DSS). Although most SB-DSS provide a powerful variety of tools for the automatic and semi-automatic analysis of simulations, visual and interactive alternatives for the manual exploration of the results are still open to further development. The work in this dissertation is focused on enhancing decision makers’ analysis capabilities by making simulation data more accessible through the incorporation of visualization and analysis techniques. To demonstrate how this goal can be achieved, two systems were developed. The first system, viPhos – standing for visualization of Phos: Greek for light –, is a system that supports lighting design in factory layout planning. viPhos combines simulation, analysis, and visualization tools and techniques to facilitate the global and local (overall factory or single workstations, respectively) interactive exploration and comparison of lighting design alternatives. The second system, STRAD - standing for Spatio-Temporal Radar -, is a web-based systems that considers the spatio/attribute-temporal analysis of event data. Since decision making processes in manufacturing also involve the monitoring of the systems over time, STRAD enables the multilevel exploration of event data (e.g., simulated or historical registers of the status of machines or results of quality control processes). A set of four case studies and one proof of concept prepared for both systems demonstrate the suitability of the visualization and analysis strategies adopted for supporting decision making processes in diverse application domains. The results of these case studies indicate that both, the systems as well as the techniques included in the systems can be generalized and extended to support the analysis of different tasks and scenarios.

The scientific and industrial interest devoted to polymer/layered silicate nanocomposites due to their outstanding properties and novel applications resulted in numerous studies in the last decade. They cover mostly thermoplastic- and thermoset-based systems. Recently, studies in rubber/layered silicate nanocomposites were started, as well. It was presented how complex maybe the nanocomposite formation for the related systems. Therefore the rules governing their structure-property relationships have to be clarified. In this Thesis, the related aspects were addressed. For the investigations several ethylene propylene diene rubbers (EPDM) of polar and non-polar origin were selected, as well as, the more polar hydrogenated acrylonitrile butadiene rubber (HNBR). The polarity was found to be beneficial on the nanocomposite formation as it assisted to the intercalation of the polymer chains within the clay galleries. This favored the development of exfoliated structures. Finding an appropriate processing procedure, i.e. compounding in a kneader instead of on an open mill, the mechanical performance of the nanocomposites was significantly improved. The complexity of the nanocomposite formation in rubber/organoclay system was demonstrated. The deintercalation of the organoclay observed, was traced to the vulcanization system used. It was evidenced by an indirect way that during sulfur curing, the primary amine clay intercalant leaves the silicate surface and migrates in the rubber matrix. This was explained by its participation in the sulfur-rich Zn-complexes created. Thus, by using quaternary amine clay intercalants (as it was presented for EPDM or HNBR compounds) the deintercalation was eliminated. The organoclay intercalation/deintercalation detected for the primary amine clay intercalants, were controlled by means of peroxide curing (as it was presented for HNBR compounds), where the vulcanization mechanism differs from that of the sulfur curing. The current analysis showed that by selecting the appropriate organoclay type the properties of the nanocomposites can be tailored. This occurs via generating different nanostructures (i.e. exfoliated, intercalated or deintercalated). In all cases, the rubber/organoclay nanocomposites exhibited better performance than vulcanizates with traditional fillers, like silica or unmodified (pristine) layered silicates.The mechanical and gas permeation behavior of the respective nanocomposites were modelled. It was shown that models (e.g. Guth’s or Nielsen’s equations) developed for “traditional” vulcanizates can be used when specific aspects are taken into consideration. These involve characteristics related to the platy structure of the silicates, i.e. their aspect ratio after compounding (appearance of platelet stacks), or their orientation in the rubber matrix (order parameter).

Collaboration aims to increase the efficiency of problem solving and decision making by bringing diverse areas of expertise together, i.e., teams of experts from various disciplines, all necessary to come up with acceptable concepts. This dissertation is concerned with the design of highly efficient computer-supported collaborative work involving active participation of user groups with diverse expertise. Three main contributions can be highlighted: (1) the definition and design of a framework facilitating collaborative decision making; (2) the deployment and evaluation of more natural and intuitive interaction and visualization techniques in order to support multiple decision makers in virtual reality environments; and (3) the integration of novel techniques into a single proof-of-concept system. Decision making processes are time-consuming, typically involving several iterations of different options before a generally acceptable solution is obtained. Although, collaboration is an often-applied method, the execution of collaborative sessions is often inefficient, does not involve all participants, and decisions are often finalized with- out the agreement of all participants. An increasing number of computer-supported cooperative work systems (CSCW) facilitate collaborative work by providing shared viewpoints and tools to solve joint tasks. However, most of these software systems are designed from a feature-oriented perspective, rather than a human-centered perspective and without the consideration of user groups with diverse experience and joint goals instead of joint tasks. The aim of this dissertation is to bring insights to the following research question: How can computer-supported cooperative work be designed to be more efficient? This question opens up more specific questions like: How can collaborative work be designed to be more efficient? How can all participants be involved in the collaboration process? And how can interaction interfaces that support collaborative work be designed to be more efficient? As such, this dissertation makes contributions in: 1. Definition and design of a framework facilitating decision making and collaborative work. Based on examinations of collaborative work and decision making processes requirements of a collaboration framework are assorted and formulated. Following, an approach to define and rate software/frameworks is introduced. This approach is used to translate the assorted requirements into a software’s architecture design. Next, an approach to evaluate alternatives based on Multi Criteria Decision Making (MCDM) and Multi Attribute Utility Theory (MAUT) is presented. Two case studies demonstrate the usability of this approach for (1) benchmarking between systems and evaluates the value of the desired collaboration framework, and (2) ranking a set of alternatives resulting from a decision-making process incorporating the points of view of multiple stake- holders. 2. Deployment and evaluation of natural and intuitive interaction and visualization techniques in order to support multiple diverse decision makers. A user taxonomy of industrial corporations serves to create a petri network of users in order to identify dependencies and information flows between each other. An explicit characterization and design of task models was developed to define interfaces and further components of the collaboration framework. In order to involve and support user groups with diverse experiences, smart de- vices and virtual reality are used within the presented collaboration framework. Natural and intuitive interaction techniques as well as advanced visualizations of user centered views of the collaboratively processed data are developed in order to support and increase the efficiency of decision making processes. The smartwatch as one of the latest technologies of smart devices, offers new possibilities of interaction techniques. A multi-modal interaction interface is provided, realized with smartwatch and smartphone in full immersive environments, including touch-input, in-air gestures, and speech. 3. Integration of novel techniques into a single proof-of-concept system. Finally, all findings and designed components are combined into the new collaboration framework called IN2CO, for distributed or co-located participants to efficiently collaborate using diverse mobile devices. In a prototypical implementation, all described components are integrated and evaluated. Examples where next-generation network-enabled collaborative environments, connected by visual and mobile interaction devices, can have significant impact are: design and simulation of automobiles and aircrafts; urban planning and simulation of urban infrastructure; or the design of complex and large buildings, including efficiency- and cost-optimized manufacturing buildings as task in factory planning. To demonstrate the functionality and usability of the framework, case studies referring to factory planning are demonstrated. Considering that factory planning is a process that involves the interaction of multiple aspects as well as the participation of experts from different domains (i.e., mechanical engineering, electrical engineering, computer engineering, ergonomics, material science, and even more), this application is suitable to demonstrate the utilization and usability of the collaboration framework. The various software modules and the integrated system resulting from the research will all be subjected to evaluations. Thus, collaborative decision making for co-located and distributed participants is enhanced by the use of natural and intuitive multi-modal interaction interfaces and techniques.