Planar force or pressure is a fundamental physical aspect during any people-vs-people and people-vs-environment activities and interactions. It is as significant as the more established linear and angular acceleration (usually acquired by inertial measurement units). There have been several studies involving planar pressure in the discipline of activity recognition, as reviewed in the first chapter. These studies have shown that planar pressure is a promising sensing modality for activity recognition. However, they still take a niche part in the entire discipline, using ad hoc systems and data analysis methods. Mostly these studies were not followed by further elaborative works. The situation calls for a general framework that can help push planar pressure sensing into the mainstream. This dissertation systematically investigates using planar pressure distribution sensing technology for ubiquitous and wearable activity recognition purposes. We propose a generic Textile Pressure Mapping (TPM) Framework, which encapsulates (1) design knowledge and guidelines, (2) a multi-layered tool including hardware, software and algorithms, and (3) an ensemble of empirical study examples. Through validation with various empirical studies, the unified TPM framework covers the full scope of application recognition, including the ambient, object, and wearable subspaces. The hardware part constructs a general architecture and implementations in the large-scale and mobile directions separately. The software toolkit consists of four heterogeneous tiers: driver, data processing, machine learning, visualization/feedback. The algorithm chapter describes generic data processing techniques and a unified TPM feature set. The TPM framework offers a universal solution for other researchers and developers to evaluate TPM sensing modality in their application scenarios. The significant findings from the empirical studies have shown that TPM is a versatile sensing modality. Specifically, in the ambient subspace, a sports mat or carpet with TPM sensors embedded underneath can distinguish different sports activities or different people's gait based on the dynamic change of body-print; a pressure sensitive tablecloth can detect various dining actions by the force propagated from the cutlery through the plates to the tabletop. In the object subspace, swirl office chairs with TPM sensors under the cover can be used to detect the seater's real-time posture; TPM can be used to detect emotion-related touch interactions for smart objects, toys or robots. In the wearable subspace, TPM sensors can be used to perform pressure-based mechanomyography to detect muscle and body movement; it can also be tailored to cover the surface of a soccer shoe to distinguish different kicking angles and intensities. All the empirical evaluations have resulted in accuracies well-above the chance level of the corresponding number of classes, e.g., the `swirl chair' study has classification accuracy of 79.5% out of 10 posture classes and in the `soccer shoe' study the accuracy is 98.8% among 17 combinations of angle and intensity.

Under the notion of Cyber-Physical Systems an increasingly important research area has evolved with the aim of improving the connectivity and interoperability of previously separate system functions. Today, the advanced networking and processing capabilities of embedded systems make it possible to establish strongly distributed, heterogeneous systems of systems. In such configurations, the system boundary does not necessarily end with the hardware, but can also take into account the wider context such as people and environmental factors. In addition to being open and adaptive to other networked systems at integration time, such systems need to be able to adapt themselves in accordance with dynamic changes in their application environments. Considering that many of the potential application domains are inherently safety-critical, it has to be ensured that the necessary modifications in the individual system behavior are safe. However, currently available state-of-the-practice and state-of-the-art approaches for safety assurance and certification are not applicable to this context. To provide a feasible solution approach, this thesis introduces a framework that allows “just-in-time” safety certification for the dynamic adaptation behavior of networked systems. Dynamic safety contracts (DSCs) are presented as the core solution concept for monitoring and synthesis of decentralized safety knowledge. Ultimately, this opens up a path towards standardized service provision concepts as a set of safety-related runtime evidences. DSCs enable the modular specification of relevant safety features in networked applications as a series of formalized demand-guarantee dependencies. The specified safety features can be hierarchically integrated and linked to an interpretation level for accessing the scope of possible safe behavioral adaptations. In this way, the networked adaptation behavior can be conditionally certified with respect to the fulfilled DSC safety features during operation. As long as the continuous evaluation process provides safe adaptation behavior for a networked application context, safety can be guaranteed for a networked system mode at runtime. Significant safety-related changes in the application context, however, can lead to situations in which no safe adaptation behavior is available for the current system state. In such cases, the remaining DSC guarantees can be utilized to determine optimal degradation concepts for the dynamic applications. For the operationalization of the DSCs approach, suitable specification elements and mechanisms have been defined. Based on a dedicated GUI-engineering framework it is shown how DSCs can be systematically developed and transformed into appropriate runtime representations. Furthermore, a safety engineering backbone is outlined to support the DSC modeling process in concrete application scenarios. The conducted validation activities show the feasibility and adequacy of the proposed DSCs approach. In parallel, limitations and areas of future improvement are pointed out.

In computer graphics, realistic rendering of virtual scenes is a computationally complex problem. State-of-the-art rendering technology must become more scalable to meet the performance requirements for demanding real-time applications. This dissertation is concerned with core algorithms for rendering, focusing on the ray tracing method in particular, to support and saturate recent massively parallel computer systems, i.e., to distribute the complex computations very efficiently among a large number of processing elements. More specifically, the three targeted main contributions are: 1. Collaboration framework for large-scale distributed memory computers The purpose of the collaboration framework is to enable scalable rendering in real-time on a distributed memory computer. As an infrastructure layer it manages the explicit communication within a network of distributed memory nodes transparently for the rendering application. The research is focused on designing a communication protocol resilient against delays and negligible in overhead, relying exclusively on one-sided and asynchronous data transfers. The hypothesis is that a loosely coupled system like this is able to scale linearly with the number of nodes, which is tested by directly measuring all possible communication-induced delays as well as the overall rendering throughput. 2. Ray tracing algorithms designed for vector processing Vector processors are to be efficiently utilized for improved ray tracing performance. This requires the basic, scalar traversal algorithm to be reformulated in order to expose a high degree of fine-grained data parallelism. Two approaches are investigated: traversing multiple rays simultaneously, and performing multiple traversal steps at once. Efficiently establishing coherence in a group of rays as well as avoiding sorting of the nodes in a multi-traversal step are the defining research goals. 3. Multi-threaded schedule and memory management for the ray tracing acceleration structure Construction times of high-quality acceleration structures are to be reduced by improvements to multi-threaded scalability and utilization of vector processors. Research is directed at eliminating the following scalability bottlenecks: dynamic memory growth caused by the primitive splits required for high- quality structures, and top-level hierarchy construction where simple task par- allelism is not readily available. Additional research addresses how to expose scatter/gather-free data-parallelism for efficient vector processing. Together, these contributions form a scalable, high-performance basis for real-time, ray tracing-based rendering, and a prototype path tracing application implemented on top of this basis serves as a demonstration. The key insight driving this dissertation is that the computational power necessary for realistic light transport for real-time rendering applications demands massively parallel computers, which in turn require highly scalable algorithms. Therefore this dissertation provides important research along the path towards virtual reality.

In this thesis we consider the directional analysis of stationary point processes. We focus on three non-parametric methods based on second order analysis which we have defined as Integral method, Ellipsoid method, and Projection method. We present the methods in a general setting and then focus on their application in the 2D and 3D case of a particular type of anisotropy mechanism called geometric anisotropy. We mainly consider regular point patterns motivated by our application to real 3D data coming from glaciology. Note that directional analysis of 3D data is not so prominent in the literature. We compare the performance of the methods, which depends on the relative parameters, in a simulation study both in 2D and 3D. Based on the results we give recommendations on how to choose the methods´ parameters in practice. We apply the directional analysis to the 3D data coming from glaciology, which consist in the locations of air-bubbles in polar ice cores. The aim of this study is to provide information about the deformation rate in the ice and the corresponding thinning of ice layers at different depths. This information is substantial for the glaciologists in order to build ice dating models and consequently to give a correct interpretation of the climate information which can be found by analyzing ice cores. In this thesis we consider data coming from three different ice cores: the Talos Dome core, the EDML core and the Renland core. Motivated by the ice application, we study how isotropic and stationary noise influences the directional analysis. In fact, due to the relaxation of the ice after drilling, noise bubbles can form within the ice samples. In this context we take two classification algorithms into consideration, which aim to classify points in a superposition of a regular isotropic and stationary point process with Poisson noise. We introduce two methods to visualize anisotropy, which are particularly useful in 3D and apply them to the ice data. Finally, we consider the problem of testing anisotropy and the limiting behavior of the geometric anisotropy transform.

Visualization is vital to the scientific discovery process. An interactive high-fidelity rendering provides accelerated insight into complex structures, models and relationships. However, the efficient mapping of visualization tasks to high performance architectures is often difficult, being subject to a challenging mixture of hardware and software architectural complexities in combination with domain-specific hurdles. These difficulties are often exacerbated on heterogeneous architectures. In this thesis, a variety of ray casting-based techniques are developed and investigated with respect to a more efficient usage of heterogeneous HPC systems for distributed visualization, addressing challenges in mesh-free rendering, in-situ compression, task-based workload formulation, and remote visualization at large scale. A novel direct raytracing scheme for on-the-fly free surface reconstruction of particle-based simulations using an extended anisoptropic kernel model is investigated on different state-of-the-art cluster setups. The versatile system renders up to 170 million particles on 32 distributed compute nodes at close to interactive frame rates at 4K resolution with ambient occlusion. To address the widening gap between high computational throughput and prohibitively slow I/O subsystems, in situ topological contour tree analysis is combined with a compact image-based data representation to provide an effective and easy-to-control trade-off between storage overhead and visualization fidelity. Experiments show significant reductions in storage requirements, while preserving flexibility for exploration and analysis. Driven by an increasingly heterogeneous system landscape, a flexible distributed direct volume rendering and hybrid compositing framework is presented. Based on a task-based dynamic runtime environment, it enables adaptable performance-oriented deployment on various platform configurations. Comprehensive benchmarks with respect to task granularity and scaling are conducted to verify the characteristics and potential of the novel task-based system design. A core challenge of HPC visualization is the physical separation of visualization resources and end-users. Using more tiles than previously thought reasonable, a distributed, low-latency multi-tile streaming system is demonstrated, being able to sustain a stable 80 Hz when streaming up to 256 synchronized 3840x2160 tiles and achieve 365 Hz at 3840x2160 for sort-first compositing over the internet, thereby enabling lightweight visualization clients and leaving all the heavy lifting to the remote supercomputer.

Various physical phenomenons with sudden transients that results into structrual changes can be modeled via switched nonlinear differential algebraic equations (DAEs) of the type \[ E_{\sigma}\dot{x}=A_{\sigma}x+f_{\sigma}+g_{\sigma}(x). \tag{DAE} \] where \(E_p,A_p \in \mathbb{R}^{n\times n}, x\mapsto g_p(x),\) is a mapping, \(p \in \{1,\cdots,P\}, P\in \mathbb{N} f \in \mathbb{R} \rightarrow \mathbb{R}^n , \sigma: \mathbb{R} \rightarrow \{1,\cdots, P\}\). Two related common tasks are: Task 1: Investigate if above (DAE) has a solution and if it is unique. Task 2: Find a connection among a solution of above (DAE) and solutions of related partial differential equations. In the linear case \(g(x) \equiv 0\) the task 1 has been tackeled already in a distributional solution framework. A main goal of the dissertation is to give contribution to task 1 for the nonlinear case \(g(x) \not \equiv 0\) ; also contributions to the task 2 are given for switched nonlinear DAEs arising while modeling sudden transients in water distribution networks. In addition, this thesis contains the following further contributions: The notion of structured switched nonlinear DAEs has been introduced, allowing also non regular distributions as solutions. This extend a previous framework that allowed only piecewise smooth functions as solutions. Further six mild conditions were given to ensure existence and uniqueness of the solution within the space of piecewise smooth distribution. The main condition, namely the regularity of the matrix pair \((E,A)\), is interpreted geometrically for those switched nonlinear DAEs arising from water network graphs. Another contribution is the introduction of these switched nonlinear DAEs as a simplication of the PDE model used classically for modeling water networks. Finally, with the support of numerical simulations of the PDE model it has been illustrated that this switched nonlinear DAE model is a good approximation for the PDE model in case of a small compressibility coefficient.

The systems in industrial automation management (IAM) are information systems. The management parts of such systems are software components that support the manufacturing processes. The operational parts control highly plug-compatible devices, such as controllers, sensors and motors. Process variability and topology variability are the two main characteristics of software families in this domain. Furthermore, three roles of stakeholders -- requirement engineers, hardware-oriented engineers, and software developers -- participate in different derivation stages and have different variability concerns. In current practice, the development and reuse of such systems is costly and time-consuming, due to the complexity of topology and process variability. To overcome these challenges, the goal of this thesis is to develop an approach to improve the software product derivation process for systems in industrial automation management, where different variability types are concerned in different derivation stages. Current state-of-the-art approaches commonly use general-purpose variability modeling languages to represent variability, which is not sufficient for IAM systems. The process and topology variability requires more user-centered modeling and representation. The insufficiency of variability modeling leads to low efficiency during the staged derivation process involving different stakeholders. Up to now, product line approaches for systematic variability modeling and realization have not been well established for such complex domains. The model-based derivation approach presented in this thesis integrates feature modeling with domain-specific models for expressing processes and topology. The multi-variability modeling framework includes the meta-models of the three variability types and their associations. The realization and implementation of the multi-variability involves the mapping and the tracing of variants to their corresponding software product line assets. Based on the foundation of multi-variability modeling and realization, a derivation infrastructure is developed, which enables a semi-automated software derivation approach. It supports the configuration of different variability types to be integrated into the staged derivation process of the involved stakeholders. The derivation approach is evaluated in an industry-grade case study of a complex software system. The feasibility is demonstrated by applying the approach in the case study. By using the approach, both the size of the reusable core assets and the automation level of derivation are significantly improved. Furthermore, semi-structured interviews with engineers in practice have evaluated the usefulness and ease-of-use of the proposed approach. The results show a positive attitude towards applying the approach in practice, and high potential to generalize it to other related domains.

In modern algebraic geometry solutions of polynomial equations are studied from a qualitative point of view using highly sophisticated tools such as cohomology, \(D\)-modules and Hodge structures. The latter have been unified in Saito’s far-reaching theory of mixed Hodge modules, that has shown striking applications including vanishing theorems for cohomology. A mixed Hodge module can be seen as a special type of filtered \(D\)-module, which is an algebraic counterpart of a system of linear differential equations. We present the first algorithmic approach to Saito’s theory. To this end, we develop a Gröbner basis theory for a new class of algebras generalizing PBW-algebras. The category of mixed Hodge modules satisfies Grothendieck’s six-functor formalism. In part these functors rely on an additional natural filtration, the so-called \(V\)-filtration. A key result of this thesis is an algorithm to compute the \(V\)-filtration in the filtered setting. We derive from this algorithm methods for the computation of (extraordinary) direct image functors under open embeddings of complements of pure codimension one subvarieties. As side results we show how to compute vanishing and nearby cycle functors and a quasi-inverse of Kashiwara’s equivalence for mixed Hodge modules. Describing these functors in terms of local coordinates and taking local sections, we reduce the corresponding computations to algorithms over certain bifiltered algebras. It leads us to introduce the class of so-called PBW-reduction-algebras, a generalization of the class of PBW-algebras. We establish a comprehensive Gröbner basis framework for this generalization representing the involved filtrations by weight vectors.

It is well known that reinforcing polymers with small amounts of nano-sized fillers is one of the most effective methods for simultaneously improving their mechanical and thermal properties. However, only a small number of studies have focused on environ-mental stress cracking (ESC), which is a major issue for premature failures of plastic products in service. Therefore, the contribution of this work focused on the influence of nano-SiO2 particles on the morphological, optical, mechanical, thermal, as well as envi-ronmental stress cracking properties of amorphous-based nanocomposites. Polycarbonate (PC), polystyrene (PS) and poly(methyl methacrylate) (PMMA) nanocom-posites containing different amounts and sizes of nano-SiO2 particles were prepared using a twin-screw extruder followed by injection molding. Adding a small amount of nano-SiO2 caused a reduction in optical properties but improved the tensile, toughness, and thermal properties of the polymer nanocomposites. The significant enhancement in mechanical and thermal properties was attributed to the adequate level of dispersion and interfacial interaction of the SiO2 nanoparticles in the polymer matrix. This situation possibly increased the efficiency of stress transfer across the nanocomposite compo-nents. Moreover, the data revealed a clear dependency on the filler size. The polymer nanocomposites filled with smaller nanofillers exhibited an outstanding enhancement in both mechanical properties and transparency compared with nanocomposites filled with larger particles. The best compromise of strength, toughness, and thermal proper-ties was achieved in PC-based nanocomposites. Therefore, special attention to the influ-ence of nanofiller on the ESC resistance was given to PC. The ESC resistance of the materials was investigated under static loading with and without the presence of stress-cracking agents. Interestingly, the incorporation of nano-SiO2 greatly enhanced the ESC resistance of PC in all investigated fluids. This result was particularly evident with the smaller quantities and sizes of nano-SiO2. The enhancement in ESC resistance was more effective in mild agents and air, where the quality of the deformation process was vastly altered with the presence of nano-SiO2. This finding confirmed that the new structural arrangements on the molecular scale in-duced by nanoparticles dominate over the ESC agent absorption effect and result in greatly improving the ESC resistance of the materials. This effect was more pronounced with increasing molecular weight of PC due to an increase in craze stability and fibril density. The most important and new finding is that the ESC behavior of polymer-based nanocomposites/ stress-cracking agent combinations can be scaled using the Hansen solubility parameter. Thus allowed us to predict the risk of ESC as a function of the filler content for different stress-cracking agents without performing extensive tests. For a comparison of different amorphous polymer-based nanocomposites at a given nano-SiO2 particle content, the ESC resistance of materials improved in the following order: PMMA/SiO2 < PS/SiO2 < low molecular weight PC/SiO2 < high molecular weight PC/SiO2. In most cases, nanocomposites with 1 vol.% of nano-SiO2 particles exhibited the largest improvement in ESC resistance. However, the remarkable improvement in the ESC resistance—particularly in PC-based nanocomposites—created some challenges related to material characterization because testing times (failure time) significantly increased. Accordingly, the superposition ap-proach has been applied to construct a master curve of crack propagation model from the available short-term tests at different temperatures. Good agreement of the master curves with the experimental data revealed that the superposition approach is a suitable comparative method for predicting slow crack growth behavior, particularly for long-duration cracking tests as in mild agents. This methodology made it possible to mini-mize testing time. Additionally, modeling and simulations using the finite element method revealed that multi-field modeling could provide reasonable predictions for diffusion processes and their impact on fracture behavior in different stress cracking agents. This finding sug-gests that the implemented model may be a useful tool for quick screening and mitigat-ing the risk of ESC failures in plastic products.

In der vorliegenden Arbeit wird das Verhalten von thermoplastischen Verbundwerkstoffen mittels experimentellen und numerischen Untersuchungen betrachtet. Das Ziel dieser Untersuchungen ist die Identifikation und Quantifikation des Versagensverhaltens und der Energieabsorptionsmechanismen von geschichteten, quasi-isotropen thermoplastischen Faser-Kunststoff-Verbunden und die Umsetzung der gewonnenen Einsichten in Eigenschaften und Verhalten eines Materialmodells zur Vorhersage des Crash-Verhaltens dieser Werkstoffe in transienten Analysen. Vertreter der untersuchten Klassen sind un- und mittel-vertreckte Rundgestricke und glasfaserverstärkte Thermoplaste (GMT). Die Untersuchungen an rundgestrickten glasfaser-(GF)-verstärktem Polyethylentherephthalat (PET) waren Teil eines Forschungsprojektes zur Charakterisierung sowohl der Verarbeitbarkeit als auch des mechanischen Verhaltens. Experimente an GMT und Schnittfaser-GMT wurden ebenfalls zum Vergleich mit dem Gestrick durchgeführt und dienen als Bestätigung des beobachteten Verhaltens des Gestrickes. Besonderer Aufmerksamkeit wird der Einfluß der Probengeometrie auf die Resultate gewidmet, weil die Crash-Charakteristiken wesentlich von der Geometrie des getesteten Probekörpers abhängen. Hierzu wurde ein Rundhutprofil zur Untersuchung dieses Einflußes definiert. Diese spezielle Geometrie hat insbesondere Vorteile hinsichtlich Energieabsorptionsvermögen sowie Herstellbarkeit von thermoplastischen Verbundwerkstoffen (TPCs). Es wurden Impakt- und Perforationsversuche zur Untersuchung der Schädigungsausbreitung und zur Charakterisierung der Zähigkeit der untersuchten Materialien durchgeführt. Geschichtete TPCs versagen hauptsächlich in einem Laminat-Biegemodus mit kombiniertem intra- und interlaminaren Schub (transversaler Schub zwischen Lagen und teilweise mit transversalen Schubbrüchen in einzelnen Lagen). Durch eine Kopplung der aktuellen Versagensmodi und Crash-Kennwerten wie der mittleren Crash-Spannung, konnten Indikationen über die Relation zwischen Materialparameter und absoluter Energieabsorption gewonnen werden. Numerische Untersuchungen wurden mit einem expliziten Finiten Elemente- Programm zur Simulation von dreidimensionalen, großen Verformungen durchgeführt. Das Modell besteht bezüglich des Querschnittaufbaus aus einer mesoskopischen Darstellung, die zwischen Matrix-zwischenlagen und mesoskopischen Verbundwerkstofflagen unterscheidet. Die Modellgeometrie stellt einen vereinfachten Längsquerschnitt durch den Probekörper dar. Dabei wurden Einflüsse der Reibung zwischen Impaktor und Material sowie zwischen einzelnen Lagen berücksichtigt. Auch die lokal herrschende Dehnrate, Energie und Spannungs-Dehnungsverteilung über die mesoskopischen Phasen konnten beobachtet werden. Dieses Modell zeigt deutlich die verschiedenen Effekte, die durch den heterogenen Charakter des Laminats entstehen, und gibt auch Hinweise für einige Erklärungen dieser Effekte. Basierend auf den Resultaten der obengenannten Untersuchungen wurde ein phänomenologisches Modell mit a-priori Information des inherenten Materialverhaltens vorgeschlagen. Daher, daß das Crashverhalten vom heterogenen Charakter des Werkstoffes dominiert wird, werden im Modell die Phasen separat betrachtet. Eine einfache Methode zur Bestimmung der mesoskopischen Eigenschaften wird diskutiert. Zur Beschreibung des Verhaltens vom thermoplastischen Matrixsystem während „Crushing“ würde ein dehnraten- und temperaturabhängiges Plastizitätsgesetz ausreichen. Für die Beschreibung des Verhaltens der Verbundwerkstoffschichten wird eine gekoppelte Plastizitäts- und Schädigungsformulierung vorgeschlagen. Ein solches Modell kann sowohl den plastischen Anteil des Matrixsystems als auch das „Softening“ - verursacht durch Faser-Matrix-Grenzflächenversagen und Faserbrüche - beschreiben. Das vorgeschlagene Modell unterscheidet zwischen Belastungsfällen für axiales „Crushing“ und Versagen ohne „Crushing“. Diese Unterteilung ermöglicht eine explizite Modellierung des Werkstoffes unter Berücksichtigung des spezifischen Materialzustandes und der Geometrie für den außerordentlichen Belastungsfall, der zum progressiven Versagen führt.

While the computing industry has shifted from single-core to multi-core processors for performance gain, safety-critical systems (SCSs) still require solutions that enable their transition while guaranteeing safety, requiring no source-code modifications and substantially reducing re-development and re-certification costs, especially for legacy applications that are typically substantial. This dissertation considers the problem of worst-case execution time (WCET) analysis under contentions when deadline-constrained tasks in independent partitioned task set execute on a homogeneous multi-core processor with dynamic time-triggered shared memory bandwidth partitioning in SCSs. Memory bandwidth in multi-core processors is shared across cores and is a significant cause of performance bottleneck and temporal variability of multiple-orders in task’s execution times due to contentions in memory sub-system. Further, the circular dependency is not only between WCET and CPU scheduling of others cores, but also between WCET and memory bandwidth assignments over time to cores. Thus, there is need of solutions that allow tailoring memory bandwidth assignments to workloads over time and computing safe WCET. It is pragmatically infeasible to obtain WCET estimates from static WCET analysis tools for multi-core processors due to the sheer computational complexity involved. We use synchronized periodic memory servers on all cores that regulate each core’s maximum memory bandwidth based on allocated bandwidth over time. First, we present a workload schedulability test for known even-memory-bandwidth-assignment-to-active-cores over time, where the number of active cores represents the cores with non-zero memory bandwidth assignment. Its computational complexity is similar to merge-sort. Second, we demonstrate using a real avionics certified safety-critical application how our method’s use can preserve an existing application’s single-core CPU schedule under contentions on a multi-core processor. It enables incremental certification using composability and requires no-source code modification. Next, we provide a general framework to perform WCET analysis under dynamic memory bandwidth partitioning when changes in memory bandwidth to cores assignment are time-triggered and known. It provides a stall maximization algorithm that has a complexity similar to a concave optimization problem and efficiently implements the WCET analysis. Last, we demonstrate dynamic memory assignments and WCET analysis using our method significantly improves schedulability compared to the stateof-the-art using an Integrated Modular Avionics scenario.

In the last decade, injection molding of long-fiber reinforced thermoplastics (LFT) has been established as a low-cost, high volume technique for manufacturing parts with complex shape without any post-treatment [1–3]. Applications are mainly found in the automotive industry with a volume annually growing by 10% to 15% [4]. While first applications were based on polyamide (PA6 and PA6.6), the market share of glass fiber reinforced polypropylene (PP) is growing due to cost savings and ease of processing. With the use of polypropylene, different processing techniques such as gas-assisted injection molding [5] or injection compression molding [6] have emerged in addition to injection molding [7, 8]. In order to overcome or justify higher materials costs when compared to short fiber reinforced thermoplastics, the manufacturing techniques for LFT pellets with fiber length greater than 10mm have evolved starting from pultrusion by improving impregnation and throughput [9] or by direct addition of fiber strands in the mold [10–12]. The benefit of long glass fiber reinforcement either in PP or PA is mainly due to the enhanced resistance to fiber pull-out resulting in an increase in impact properties and strength [13–19], even at low temperature levels [20]. Creep and fatigue resistance are also substantially improved [21, 22]. The performance of fiber reinforced thermoplastics manufactured by injection molding strongly depends on the flow-induced microstructure which is driven by materials composition, processing conditions and part geometry. The anisotropic microstructure is characterized by fiber fraction and dispersion, fiber length and fiber orientation. Facing the complexity of this processing technique, simulation becomes a precious tool already in the concept phase for parts manufactured by injection molding. Process simulation supports decisions with respect to choice of concepts and materials. The part design is determined in terms of mold filling including location of gates, vents and weld lines. Tool design requires the determination of melt feeding, logistics and mold heating. Subsequently, performance including prediction of shrinkage and warpage as well as structural analysis is evaluated [23]. While simulation based on two-dimensional representation of three-dimensional part geometry has been extensively used during the last two decades, the complexity of the parts as well as the trend towards solid modelling in CAD and CAE demands the step towards three-dimensional process simulation. The scope of this work is the prediction of flow-induced microstructure during injection molding of long glass fiber reinforced polypropylene using threedimensional process simulation. Modelling of the injection molding process in three dimensions is supported experimentally by rheological characterization in both shear and extensional flow and by two- and three-dimensional evaluation of microstructure. In chapter 2 the fundamentals of rheometry and rheology are presented with respect to long fiber reinforced thermoplastics. The influence of parameters on microstructure is described and approaches for modelling the state of microstructure and its dynamics are discussed. Chapter 3 introduces a rheometric technique allowing for rheological characterization of polymer melts at processing conditions as encountered during manufacturing. Using this rheometer, both shear and extensional viscosity of long glass fiber reinforced polypropylene are measured with respect to composition of materials, processing conditions and geometry of the cavity. Chapter 4 contains the evaluation of microstructure of long glass fiber reinforced polypropylene in terms of two-dimensional fiber orientation and its dependence on materials parameters and processing condition. For the evaluation of three-dimensional microstructure, a technique based on x-ray tomography is introduced. In chapter 5, modelling of microstructural dynamics is addressed. One-way coupling of interactions between fluid and fibers is described macroscopically. The flow behavior of fibers in the vicinity of cavity walls is evaluated experimentally. From these observations, a model for treatment of fiber-wall interaction with respect to numerical simulation is proposed. Chapter 6 presents the application of three-dimensional simulation of the injection molding process. Mold filling simulation is performed using a commercial code while prediction of 3D fiber orientation is based on a proprietary module. The rheological and thermal properties derived in chapter 3 are tested by simulation of the experiments and comparison of predicted pressure and temperature profile versus recorded results. The performance of fiber orientation prediction is verified using analytical solutions of test examples from literature. The capability of three-dimensional simulation is demonstrated based on the simulation of mold filling and prediction of fiber orientation for an automotive part.

Wine and alcoholic fermentations are complex and fascinating ecosystems. Wine aroma is shaped by the wine’s chemical compositions, in which both microbes and grape constituents play crucial roles. Activities of the microbial community impact the sensory properties of the final product, therefore, the characterisation of microbial diversity is essential in understanding and predicting sensory properties of wine. Characterisation has been challenging with traditional approaches, where microbes are isolated and therefore analyzed outside from their natural environment. This causes a bias in the observed microbial composition structure. In addition, true community interactions cannot be studied using isolates. Furthermore, the multiplex ties between wine chemical and sensory compositions remain evasive due to their multivariate and nonlinear nature. Therefore, the sensorial outcome arising from different microbial communities has remained inconclusive. In this thesis, microbial diversity during Riesling wine fermentations is investigated with the aim to understand the roles of microbial communities during fermentations and their links to sensory properties. With the advancement of high-throughput tools based ‘omic methods, such as next-generation sequencing (NGS) technologies, it is now possible to study microbial communities and their functions without isolation by culturing. This developing field and its potential to wine community is reviewed in Chapter 1. The standardisation of methods remains challenging in the field. DNA extraction is a key step in capturing the microbial diversity in samples for generating NGS data, therefore, DNA extraction methods are evaluated in Chapter 2. In Chapter 3, machine learning is utilized in guiding raw data mining generated by the untargeted GC-MS analysis. This step is crucial in order to take full advantages of the large scope of data generated by ‘omic methods. These lay a solid foundation for Chapters 4 and 5 where microbial community structures and their outputs - chemical and sensory compositions are studied by using approaches and tools based on multiple ‘omics methods. The results of this thesis show first that by using novel statistical approaches, it is possible to extract meaningful information from heterogeneous biological, chemical and sensorial data. Secondly, results suggest that the variation in wine aroma, might be related to microbial interactions taking place not only inside a single community, but also the IV interactions between communities, such as vineyard and winery communities. Therefore, the true sensory expression of terroir might be masked by the interaction between two microbial communities, although more work is needed to uncover this potential relationship. Such potential interaction mechanisms were uncovered between non- Saccharomyces yeast and bacteria in this work and unexpected novel bacterial growth was observed during alcohol fermentation. This suggests new layers in understanding of wine fermentations. In the future, multi-omic approaches could be applied to identify biological pathways leading to specific wine aroma as well as investigate the effects upon specific winemaking conditions. These results are relevant not just for the wine industry, but also to other industries where complex microbial networks are important. As such, the approaches presented in this thesis might find widely use in the food industry. 


MsmS is a heme-based redox sensor kinase in Methanosarcina acetivorans consisting of alternating PAS and GAF domains connected to a C-terminal kinase domain. In addition to MsmS, M. acetivorans possesses a second kinase, MA0863 with high sequence similarity. Interestingly, MA0863 possesses an amber codon in its second GAF domain, encoding for the amino acid pyrrolysine. Thus far, no function of this residue has been resolved. In order to examine the heme iron coordination in both proteins, an improved method for the production of heme proteins was established using the Escherichia coli strain Nissle 1917. This method enables the complete reconstitution of a recombinant hemoprotein during protein production, thereby resulting in a native heme coordination. Analysis of the full-length MsmS and MA0863 confirmed a covalently bound heme cofactor, which is connected to one conserved cysteine residue in each protein. In order to identify the coordinating amino acid residues of the heme iron, UV/vis spectra of different variants were measured. These studies revealed His702 in MsmS and the corresponding His666 in MA0863 as the proximal heme ligands. MsmS has previously been described as a heme-based redox sensor. In order to examine whether the same is true for MA0863, redox dependent kinase assays were performed. MA0863 indeed displays redox dependent autophosphorylation activity, which is independent of heme ligands and only observed under oxidizing conditions. Interestingly, autophosphorylation was shown to be independent of the heme cofactor but rather relies on thiol oxidation. Therefore, MA0863 was renamed in RdmS (redox dependent methyltransferase-associated sensor). In order to identify the phosphorylation site of RdmS, thin layer chromatography was performed identifying a tyrosine as the putative phosphorylation site. This observation is in agreement with the lack of a so-called H-box in typical histidine kinases. Due to their genomic localization, MsmS and RdmS were postulated to form two-component systems (TCS) with vicinal encoded regulator proteins MsrG and MsrF. Therefore, protein-protein interaction studies using the bacterial adenylate two hybrid system were performed suggesting an interaction of RdmS and MsmS with the three regulators MsrG/F/C. Due to these multiple interactions these signal transduction pathways should rather be considered multicomponent system instead of two component systems.

Study 1 (Chapter 2) is an empirical case study that concerns the nature of teaching–learning transactions that facilitate self-directed learning in vocational education and training of young adults in England. It addresses in part the concern that fostering the skills necessary for self-directed learning is an important endeavor of vocational education and training in many contexts internationally. However, there is a distinct lack of studies that investigate the extent to which facilitation of self-directed learning is present within vocational education and training in different contexts. An exploratory thematic qualitative analysis of inspectors’ comments within general Further Education college Ofsted inspection reports was conducted to investigate the balance of control of the learning process between teacher and learner within vocational education and training of young adults in England. A clear difference between outstanding and inadequate provision is reported. Inadequate provision was overwhelmingly teacher-directed. Outstanding provision reflected a collaborative relationship between teacher and learner in directing the learning process, despite the Ofsted framework not explicitly identifying the need for learner involvement in directing the learning process. The chapter offers insight into the understanding of how an effective balance of control of learning between teacher and learner may be realized in vocational education and training settings and highlights the need to consider the modulating role of contextual factors. Following the further research directions outlined in Chapter 2, study 2 (Chapter 3) is a theoretical chapter that addresses the issue that fostering adult learners’ competence to adapt appropriately to our ever-changing world is a primary concern of adult education. The purpose of the chapter is novel and examines whether the consideration of modes of learning (instruction, performance, and inquiry) could assist in the design of adult education that facilitates self-directed learning and enables learners to think and perform adaptively. The concept of modes of learning originated from the typology of Houle (1980). However, to date, no study has reached beyond this typology, especially concerning the potential of using modes of learning in the design of adult education. Specifically, an apparent oversight in adult learning theory is the foremost importance of the consideration of whether inquiry is included in the learning process: its inclusion potentially differentiates the purpose of instruction, the nature of learners’ performance, and the underlying epistemological positioning. To redress this concern, two models of modes of learning are proposed and contrasted. The reinforcing model of modes of learning (instruction, performance, without inquiry) promotes teacher-directed learning. A key consequence of employing this model in adult education is that learners may become accustomed to habitually reinforcing patterns of perceiving, thinking, judging, feeling, and acting—performance that may be rather inflexible and represented by a distinct lack of a perceived need to adapt to social contextual changes: a lack of motivation for self-directed learning. Rather, the adapting model of modes of learning (instruction, performance, with inquiry) may facilitate learners to be adaptive in their performance—by encouraging an enhanced learner sensitivity toward changing social contextual conditions: potentially enhancing learners’ motivation for self-directed learning. In line with the further research directions highlighted in Chapter 3, concerning the need to consider the nature and treatment of educational experiences that are conductive to learner growth and development, study 3 (Chapter 4) presents a systematic review of the experiential learning theory; a theory that perhaps cannot be uncoupled from self-directed learning theory, especially in regard to understanding the cognitive aspect of self-directed learning, which represents an important direction for further research on self-directed learning. D. A. Kolb’s (1984) experiential learning cycle is perhaps the most scholarly influential and cited model regarding experiential learning theory. However, a key issue in interpreting Kolb’s model concerns a lack of clarity regarding what constitutes a concrete experience, exactly. A systematic literature review was conducted in order to examine: what constitutes a concrete experience and what is the nature of treatment of a concrete experience in experiential learning? The analysis revealed five themes: learners are involved, active, participants; knowledge is situated in place and time; learners are exposed to novel experiences, which involves risk; learning demands inquiry to specific real-world problems; and critical reflection acts as a mediator of meaningful learning. Accordingly, a revision to Kolb’s model is proposed: experiential learning consists of contextually rich concrete experience, critical reflective observation, contextual-specific abstract conceptualization, and pragmatic active experimentation. Further empirical studies are required to test the model proposed. Finally, in Chapter 5 key findings of the studies are summarized, including that the models proposed in Chapters 3 and 4 (Figures 2 and 4, respectively) may be important considerations for further research on self-directed learning.

Graphs and flow networks are important mathematical concepts that enable the modeling and analysis of a large variety of real world problems in different domains such as engineering, medicine or computer science. The number, sizes and complexities of those problems permanently increased during the last decades. This led to an increased demand of techniques that help domain experts in understanding their data and its underlying structure to enable an efficient analysis and decision making process. To tackle this challenge, this work presents several new techniques that utilize concepts of visual analysis to provide domain scientists with new visualization methodologies and tools. Therefore, this work provides novel concepts and approaches for diverse aspects of the visual analysis such as data transformation, visual mapping, parameter refinement and analysis, model building and visualization as well as user interaction. The presented techniques form a framework that enriches domain scientists with new visual analysis tools and help them analyze their data and gain insight from the underlying structures. To show the applicability and effectiveness of the presented approaches, this work tackles different applications such as networking, product flow management and vascular systems, while preserving the generality to be applicable to further domains.

Ever since establishment of portfolio selection theory by Markowitz (1952), the use of Standard deviation as a measure of risk has heavily been criticized. The aim of this thesis is to refine classical portfolio selection and asset pricing theory by using a downside deviation risk measure. It is defined as below-target semideviation and referred to as downside risk. Downside efficient portfolios maximize expected payoff given a prescribed upper bound for downside risk and, thus, are analogs to mean-variance efficient portfolios in the sense of Markowitz. The present thesis provides an alternative proof of existence of downside efficient portfolios and identifies a sufficient criterion for their uniqueness. A specific representation of their form brings structural similarity to mean-variance efficient portfolios to light. Eventually, a separation theorem for the existence and uniqueness of portfolios that maximize the trade-off between downside risk and return is established. The notion of a downside risk asset market equilibrium (DRAME) in an asset market with finitely many investors is introduced. This thesis addresses the existence and uniqueness Problem of such equilibria and specifies a DRAME pricing formula. In contrast to prices obtained from the mean-variance CAPM pricing formula, DRAME prices are arbitrage-free and strictly positive. The final part of this thesis addresses practical issues. An algorithm that allows for an effective computation of downside efficient portfolios from simulated or historical financial data is outlined. In a simulation study, it is revealed in which scenarios downside efficient portfolios outperform mean-variance efficient portfolios.

The fact that long fibre reinforced thermoplastic composites (LFT) have higher tensile strength, modulus and even toughness, compared to short fibre reinforced thermoplastics with the same fibre loading has been well documented in literature. These are the underlying factors that have made LFT materials one of the most rapidly growing sectors of plastics industry. New developments in manufacturing of LFT composites have led to improvements in mechanical properties and price reduction, which has made these materials an attractive choice as a replacement for metals in automobile parts and other similar applications. However, there are still several open scientific questions concerning the material selection leading to the optimal property combinations. The present work is an attempt to clarify some of these questions. The target was to develop tools that can be used to modify, or to “tailor”, the properties of LFT composite materials, according to the requirements of automobile and other applications. The present study consisted of three separate case studies, focusing on the current scientific issues on LFT material systems. The first part of this work was focused on LGF reinforced thermoplastic styrenic resins. The target was to find suitable maleic acid anhydride (MAH) based coupling agents in order to improve the fibre-matrix interfacial strength, and, in this way, to develop an LGF concentrate suitable for thermoplastic styrenic resins. It was shown that the mechanical properties of LGF reinforced “styrenics” were considerably improved when a small amount of MAH functionalised polymer was added to the matrix. This could be explained by the better fibre-matrix adhesion, revealed by scanning electron microscopy of fracture surfaces. A novel LGF concentrate concept showed that one particular base material can be used to produce parts with different mechanical and thermal properties by diluting the fibre content with different types of thermoplastic styrenic resins. Therefore, this concept allows a flexible production of parts, and it can be used in the manufacturing of interior parts for automobile components.The second material system dealt with so called hybrid composites, consisting of long glass fibre reinforced polypropylene (LGF-PP) and mineral fillers like calcium carbonate and talcum. The aim was to get more information about the fracture behaviour of such hybrid composites under tensile and impact loading, and to observe the influence of the fillers on properties. It was found that, in general, the addition of fillers in LGF-PP, increased stiffness but the strength and fracture toughness were decreased. However, calcium carbonate and talcum fillers resulted in different mechanical properties, when added to LGF-PP: better mechanical properties were achieved by using talcum, compared to calcium carbonate. This phenomenon could be explained by the different nucleation effect of these fillers, which resulted in a different crystalline morphology of polypropylene, and by the particle orientation during the processing when talc was used. Furthermore, the acoustic emission study revealed that the fracture mode of LGF-PP changed when calcium carbonate was added. The characteristic acoustic signals revealed that the addition of filler led to the fibre debonding at an earlier stage of fracture sequence when compared to unfilled LGF-PP. In the third material system, the target was to develop a novel long glass fibre reinforced composite material based on the blend of polyamide with thermoset resins. In this study a blend of polyamide-66 (PA66) and phenol formaldehyde resin (PFR) was used. The chemical structure of the PA66-PFR resin was analysed by using small molecular weight analogues corresponding to PA66 and PFR components, as well as by carrying out experiments using the macromolecular system. Theoretical calculations and experiments showed that there exists a strong hydrogen bonding between the carboxylic groups of PA66 and the hydroxylic groups of PFR, exceeding even the strength of amide-water hydrogen bonds. This was shown to lead to the miscible blends, when PFR was not crosslinked. It was also found that the morphology of such thermoplastic-thermoset blends can be controlled by altering ratio of blend components (PA66, PFR and crosslinking agent). In the next phase, PA66-PFR blends were reinforced by long glass fibres. The studies showed that the water absorption of the blend samples was considerably decreased, which was also reflected in higher mechanical properties at equilibrium state. Wie man aus zahlreichen Untersuchungen und Anwendungsbeispielen entnehmen kann, besitzen langfaserverstärkte Thermoplaste (LFT) eine bessere Zugfestigkeit, Biege- und Schlagzähigkeit im Vergleich zu kurzfaserverstärkten Thermoplasten. Die Vorteile in den mechanischen Eigenschaften haben die LFT zu einem schnellwachsenden Bereich in der Kunststoffindustrie gemacht. Neue Entwicklungen in Bereich der Herstellung von LFT haben für zusätzliche Verbesserungen der mechanischen Eigenschaften sowie eine Preisreduzierung der Materialien in den vergangenen Jahren gesorgt, was die LFT zu einer attraktiven Wahl u.a. als Ersatz von Metallen in Automobilteilen macht. Es stellen sich allerdings immer noch einige offene wissenschaftliche Fragen in Bezug auf z.B. die Materialbeschaffenheit, um optimale Eigenschaftskombinationen zu erreichen. Die vorliegende Arbeit versucht, einige dieser Fragen zu beantworten. Ziel war es, Vorgehensweisen zu entwickeln, mit denen man die Eigenschaften von LFT gezielt beeinflussen und so den Anforderungen von Automobilen oder anderen Anwendungen anpassen oder „maßschneidern“ kann. Die vorliegende Arbeit besteht aus drei Teilen, welche sich auf unterschiedliche Materialsysteme, angepasst an den aktuellen Bedarf und das Interesse der Industrie, konzentrieren. Der erste Teil der Arbeit richtet sich auf die Eigenschaftsoptimierung von langglasfaserverstärkten (LGF) thermoplastischen Styrolcopolymeren und von Blends aus diesen Materialien. Es wurden passende, auf Maleinsäureanhydride (MAH) basierende Kopplungsmittel gefunden, um die Faser-Matrix-Haftung zu optimieren. Weiterhin wurde ein LGF Konzentrat entwickelt, welches mit verschiedenen thermoplastischen Styrolcopolymeren kompatibel ist und somit als „Verstärkungsadditiv“ eingesetzt werden kann.Das Konzept für ein neues LGF-Konzentrat auf Basis des kompatiblen Materialsystems konzentriert sich insbesondere darauf, dass ein Basismaterial für die Herstellung von Bauteilen bereit gestellt werden kann, mit dessen Hilfe gezielt verschiedene mechanische und thermomechanischen Eigenschaften durch das Zumischen von verschiedenen Styrolcopoylmeren und Blends verbessert werden können. Dieses Konzept ermöglicht eine sehr flexible Produktion von Bauteilen und wird seine Anwendung bei der Herstellung von Bauteilen u.a. im Interieur von Autos finden. Das zweite Materialsystem basiert auf sogenannten hybriden Verbundwerkstoffen, welche aus Langglasfasern und mineralischen Füllstoffen wie Kalziumkarbonat und Talkum in einer Polypropylen (PP) - Matrix zusammengesetzt sind. Ziel war es, durch detaillierte bruchmechanische Analysen genaue Informationen über das Bruchverhalten dieser hybriden Verbundwerkstoffe bei Zug- und Schlagbelastung zu bekommen, um dann die Unterschiede zwischen den verschiedenen Füllstoffen in Bezug auf ihre Eigenschaften zu dokumentieren. Es konnte beobachtet werden, dass bei Zugabe der Füllstoffe zum LGF-PP normalerweise die Steifigkeit weiter verbessert wurde, jedoch die Festigkeit und Schlagzähigkeit abnahmen. Weiterhin zeigten die verschiedenen Füllstoffe wie Kalziumkarbonat und Talkum unterschiedliche mechanische Eigenschaften auf, wenn sie zusammen mit LGF Verstärkung eingesetzt wurden: Bei der Zugabe von Talkum wurde u.a. eine deutlich bessere Schlagzähigkeit als bei der Zugabe von Kalziumkarbonat festgestellt. Dieses Phänomen konnte durch das unterschiedliche Nukleierungsverhalten des PPs erklärt werden, welches in einer unterschiedlichen Kristallmorphologie von Polypropylen resultierte. Weiterhin konnte man durch Messungen der akustischen Emmissionen während der Zugbelastung eines bruchmechanischen Versuchskörpers aufzeigen, dass die höhere Bruchzähigkeit von LGF-PP ohne Füllstoffe daraus resultiert, dass Faser-Pullout schon bei geringeren Kräften vorhanden war.

Materials in general can be divided into insulators, semiconductors and conductors, depending on their degree of electrical conductivity. Polymers are classified as electrically insulating materials, having electrical conductivity values lower than 10-12 S/cm. Due to their favourable characteristics, e.g. their good physical characteristics, their low density, which results in weight reduction, etc., polymers are also considered for applications where a certain degree of conductivity is required. The main aim of this study was to develop electrically conductive composite materials based on epoxy (EP) matrix, and to study their thermal, electrical, and mechanical properties. The target values of electrical conductivity were mainly in the range of electrostatic discharge protection (ESD, 10-9-10-6 S/cm). Carbon fibres (CF) were the first type of conductive filler used. It was established that there is a significant influence of the fibre aspect ratio on the electrical properties of the fabricated composite materials. With longer CF the percolation threshold value could be achieved at lower concentrations. Additional to the homogeneous CF/EP composites, graded samples were also developed. By the use of a centrifugation method, the CF created a graded distribution along one dimension of the samples. The effect of the different processing parameters on the resulting graded structures and consequently on their gradients in the electrical and mechanical properties were systematically studied. An intrinsically conductive polyaniline (PANI) salt was also used for enhancing the electrical properties of the EP. In this case, a much lower percolation threshold was observed compared to that of CF. PANI was found out to have, up to a particular concentration, a minimal influence on the thermal and mechanical properties of the EP system. Furthermore, the two above-mentioned conductive fillers were jointly added to the EP matrix. Improved electrical and mechanical properties were observed by this incorporation. A synergy effect between the two fillers took place regarding the electrical conductivity of the composites. The last part of this work was engaged in the application of existing theoretical models for the prediction of the electrical conductivity of the developed polymer composites. A good correlation between the simulation and the experiments was observed. Allgemein werden Materialien in Bezug auf ihre elektrische Leitfähigkeit in Isolatoren, Halbleiter oder Leiter unterteilt. Polymere gehören mit einer elektrischen Leitfähigkeit niedriger als 10-12 S/cm in die Gruppe der Isolatoren. Aufgrund vorteilhafter Eigenschaften der Polymere, wie z.B. ihren guten physikalischen Eigenschaften, ihrer geringen Dichte, welche zur Gewichtsreduktion beiträgt, usw., werden Polymere auch für Anwendungen in Betracht gezogen, bei denen ein gewisser Grad an Leitfähigkeit gefordert wird. Das Hauptziel dieser Studie war, elektrisch leitende Verbundwerkstoffe auf der Basis von Epoxidharz (EP) zu entwickeln und deren elektrische, mechanische und thermische Eigenschaften zu studieren. Die Zielwerte der elektrischen Leitfähigkeit lagen hauptsächlich im Bereich der Vermeidung elektrostatischer Aufladungen (ESD, 10-9-10-6 S/cm). Bei der Herstellung elektrisch leitender Kunststoffen wurden als erstes Kohlenstofffasern (CF) als leitfähige Füllstoffe benutzt. Bei den durchgeführten Experimenten konnte man beobachten, dass das Faserlängenverhältnis einen bedeutenden Einfluss auf die elektrischen Eigenschaften der fabrizierten Verbundwerkstoffe hat. Mit längeren CF wurde die Perkolationsschwelle bereits bei einer niedrigeren Konzentration erreicht. Zusätzlich zu den homogenen CF/EP Verbundwerkstoffen, wurden auch Gradientenwerkstoffe entwickelt. Mit Hilfe einer Zentrifugation konnte eine gradierte Verteilung der CF entlang der Probenlängeachse erreicht werden. Die Effekte der unterschiedlichen Zentrifugationsparameter auf die resultierenden Gradientenwerkstoffe und die daraus resultierenden, gradierten elektrischen und mechanischen Eigenschaften wurden systematisch studiert. Ein intrinsisch leitendes Polyanilin-Salz (PANI) wurde auch für das Erhöhen der elektrischen Eigenschaften des EP benutzt. In diesem Fall wurde eine viel niedrigere Perkolationsschwelle verglichen mit der von CF beobachtet. Der Einsatz von PANI hat bis zu einer bestimmten Konzentration nur einen minimalen Einfluß auf die thermischen und mechanischen Eigenschaften des EP Systems. In einem dritte Schritt wurden die zwei oben erwähnten, leitenden Füllstoffe gemeinsam der EP Matrix hinzugefügt. Erhöhte elektrische und mechanische Eigenschaften wurden in diesem Fall beobachtet, wobei sich ein Synergie-Effekt zwischen den zwei Füllstoffen bezogen auf die elektrische Leitfähigkeit der Verbundwerkstoffe ergab. Im letzten Teil dieser Arbeit fand die Anwendung von theoretischen Modelle zur Vorhersage der elektrischen Leitfähigkeit der entwickelten Verbundwerkstoffe statt. Dabei konnte eine gute Übereinstimmung mit den experimentellen Ergebnissen festgestellt werden .

The demand of sustainability is continuously increasing. Therefore, thermoplastic composites became a focus of research due to their good weight to performance ratio. Nevertheless, the limiting factor of their usage for some processes is the loss of consolidation during re-melting (deconsolidation), which reduces the part quality. Several studies dealing with deconsolidation are available. These studies investigate a single material and process, which limit their usefulness in terms of general interpretations as well as their comparability to other studies. There are two main approaches. The first approach identifies the internal void pressure as the main cause of deconsolidation and the second approach identifies the fiber reinforcement network as the main cause. Due to of their controversial results and limited variety of materials and processes, there is a big need of a more comprehensive investigation on several materials and processes. This study investigates the deconsolidation behavior of 17 different materials and material configurations considering commodity, engineering, and performance polymers as well as a carbon and two glass fiber fabrics. Based on the first law of thermodynamics, a deconsolidation model is proposed and verified by experiments. Universal applicable input parameters are proposed for the prediction of deconsolidation to minimize the required input measurements. The study revealed that the fiber reinforcement network is the main cause of deconsolidation, especially for fiber volume fractions higher than 48 %. The internal void pressure can promote deconsolidation, when the specimen was recently manufactured. In other cases the internal void pressure as well as the surface tension prevents deconsolidation. During deconsolidation the polymer is displaced by the volume increase of the void. The polymer flow damps the progress of deconsolidation because of the internal friction of the polymer. The crystallinity and the thermal expansion lead to a reversible thickness increase during deconsolidation. Moisture can highly accelerate deconsolidation and can increase the thickness by several times because of the vaporization of water. The model is also capable to predict reconsolidation under the defined boundary condition of pressure, time, and specimen size. For high pressure matrix squeeze out occur, which falsifies the accuracy of the model.The proposed model was applied to thermoforming, induction welding, and thermoplastic tape placement. It is demonstrated that the load rate during thermoforming is the critical factor of achieving complete reconsolidation. The required load rate can be determined by the model and is dependent on the cooling rate, the forming length, the extent of deconsolidation, the processing temperature, and the final pressure. During induction welding deconsolidation can tremendously occur because of the left moisture in the polymer at the molten state. The moisture cannot fully diffuse out of the specimen during the faster heating. Therefore, additional pressure is needed for complete reconsolidation than it would be for a dry specimen. Deconsolidation is an issue for thermoplastic tape placement, too. It limits the placement velocity because of insufficient cooling after compaction. If the specimen after compaction is locally in a molten state, it deconsolidates and causes residual stresses in the bond line, which decreases the interlaminar shear strength. It can be concluded that the study gains new knowledge and helps to optimize these processes by means of the developed model without a high number of required measurements. Aufgrund seiner guten spezifischen Festigkeit und Steifigkeit ist der endlosfaserverstärkte Thermoplast ein hervorragender Leichtbauwerkstoff. Allerdings kann es während des Wiederaufschmelzens durch Dekonsolidierung zu einem Verlust der guten mechanischen Eigenschaften kommen, daher ist Dekonsolidierung unerwünscht. In vielen Studien wurde die Dekonsolidierung mit unterschiedlichen Ergebnissen untersucht. Dabei wurde meist ein Material und ein Prozess betrachtet. Eine allgemeine Interpretation und die Vergleichbarkeit unter den Studien sind dadurch nur begrenzt möglich. Aus der Literatur sind zwei Ansätze bekannt. Dem ersten Ansatz liegt der Druckunterschied zwischen Poreninnendruck und Umgebungsdruck als Hauptursache der Dekonsolidierung zu Grunde. Beim zweiten Ansatz wird die Faserverstärkung als Hauptursache identifiziert. Aufgrund der kontroversen Ergebnisse und der begrenzten Anzahl der Materialien und Verarbeitungsverfahren, besteht die Notwendigkeit einer umfassenden Untersuchung über mehrere Materialien und Prozesse. Diese Studie umfasst drei Polymere (Polypropylen, Polycarbonat und Polyphenylensulfid), drei Gewebe (Köper, Atlas und Unidirektional) und zwei Prozesse (Autoklav und Heißpressen) bei verschiedenen Faservolumengehalten. Es wurde der Einfluss des Porengehaltes auf die interlaminare Scherfestigkeit untersucht. Aus der Literatur ist bekannt, dass die interlaminare Scherfestigkeit mit der Zunahme des Porengehaltes linear sinkt. Dies konnte für die Dekonsolidierung bestätigt werden. Die Reduktion der interlaminaren Scherfestigkeit für thermoplastische Matrizes ist kleiner als für duroplastische Matrizes und liegt im Bereich zwischen 0,5 % bis 1,5 % pro Prozent Porengehalt. Außerdem ist die Abnahme signifikant vom Matrixpolymer abhängig. Im Falle der thermisch induzierten Dekonsolidierung nimmt der Porengehalt proportional zu der Dicke der Probe zu und ist ein Maß für die Dekonsolidierung. Die Pore expandiert aufgrund der thermischen Gasexpansion und kann durch äußere Kräfte zur Expansion gezwungen werden, was zu einem Unterdruck in der Pore führt. Die Faserverstärkung ist die Hauptursache der Dickenzunahme beziehungsweise der Dekonsolidierung. Die gespeicherte Energie, aufgebaut während der Kompaktierung, wird während der Dekonsolidierung abgegeben. Der Dekompaktierungsdruck reicht von 0,02 MPa bis 0,15 MPa für die untersuchten Gewebe und Faservolumengehalte. Die Oberflächenspannung behindert die Porenexpansion, weil die Oberfläche vergrößert werden muss, die zusätzliche Energie benötigt. Beim Kontakt von benachbarten Poren verursacht die Oberflächenspannung ein Verschmelzen der Poren. Durch das bessere Volumen- Oberfläche-Verhältnis wird Energie abgebaut. Der Polymerfluss bremst die Entwicklung der Dickenzunahme aufgrund der erforderlichen Energie (innere Reibung) der viskosen Strömung. Je höher die Temperatur ist, desto niedriger ist die Viskosität des Polymers, wodurch weniger Energie für ein weiteres Porenwachstum benötigt wird. Durch den reversiblen Einfluss der Kristallinität und der Wärmeausdehnung des Verbundes wird während der Erwärmung die Dicke erhöht und während der Abkühlung wieder verringert. Feuchtigkeit kann einen enormen Einfluss auf die Dekonsolidierung haben. Ist noch Feuchtigkeit über der Schmelztemperatur im Verbund vorhanden, verdampft diese und kann die Dicke um ein Vielfaches der ursprünglichen Dicke vergrößern. Das Dekonsolidierungsmodell ist in der Lage die Rekonsolidierung vorherzusagen. Allerdings muss der Rekonsolidierungsdruck unter einem Grenzwert liegen (0,15 MPa für 50x50 mm² und 1,5 MPa für 500x500 mm² große Proben), da es sonst bei der Probe zu einem Polymerfluss aus der Probe von mehr als 2 % kommt. Die Rekonsolidierung ist eine inverse Dekonsolidierung und weist die gleichen Mechanismen in der entgegengesetzten Richtung auf. Das entwickelte Modell basiert auf dem ersten Hauptsatz der Thermodynamik und kann die Dicke während der Dekonsolidierung und der Rekonsolidierung vorhersagen. Dabei wurden eine homogene Porenverteilung und eine einheitliche, kugelförmige Porengröße angenommen. Außerdem wurde die Massenerhaltung angenommen. Um den Aufwand für die Bestimmung der Eingangsgrößen zu reduzieren, wurden allgemein gültige Eingabeparameter bestimmt, die für eine Vielzahl von Konfigurationen gelten. Das simulierte Materialverhalten mit den allgemein gültigen Eingangsparametern erzielte unter den definierten Einschränkungen eine gute Übereinstimmung mit dem tatsächlichen Materialverhalten. Nur bei Konfigurationen mit einer Viskositätsdifferenz von mehr als 30 % zwischen der Schmelztemperatur und der Prozesstemperatur sind die allgemein gültigen Eingangsparameter nicht anwendbar. Um die Relevanz für die Industrie aufzuzeigen, wurden die Effekte der Dekonsolidierung für drei weitere Verfahren simuliert. Es wurde gezeigt, dass die Kraftzunahmegeschwindigkeit während des Thermoformens ein Schlüsselfaktor für eine vollständige Rekonsolidierung ist. Wenn die Kraft zu langsam appliziert wird oder die finale Kraft zu gering ist, ist die Probe bereits erstarrt, bevor eine vollständige Konsolidierung erreicht werden kann. Auch beim Induktionsschweißen kann Dekonsolidierung auftreten. Besonders die Feuchtigkeit kann zu einer starken Zunahme der Dekonsolidierung führen, verursacht durch die sehr schnellen Heizraten von mehr als 100 K/min. Die Feuchtigkeit kann während der kurzen Aufheizphase nicht vollständig aus dem Polymer ausdiffundieren, sodass die Feuchtigkeit beim Erreichen der Schmelztemperatur in der Probe verdampft. Beim Tapelegen wird die Ablegegeschwindigkeit durch die Dekonsolidierung begrenzt. Nach einer scheinbar vollständigen Konsolidierung unter der Walze kann die Probe lokal dekonsolidieren, wenn das Polymer unter der Oberfläche noch geschmolzen ist. Die daraus resultierenden Poren reduzieren die interlaminare Scherfestigkeit drastisch um 5,8 % pro Prozent Porengehalt für den untersuchten Fall. Ursache ist die Kristallisation in der Verbindungszone. Dadurch werden Eigenspannungen erzeugt, die in der gleichen Größenordnung wie die tatsächliche Scherfestigkeit sind.

Novel image processing techniques have been in development for decades, but most of these techniques are barely used in real world applications. This results in a gap between image processing research and real-world applications; this thesis aims to close this gap. In an initial study, the quantification, propagation, and communication of uncertainty were determined to be key features in gaining acceptance for new image processing techniques in applications. This thesis presents a holistic approach based on a novel image processing pipeline, capable of quantifying, propagating, and communicating image uncertainty. This work provides an improved image data transformation paradigm, extending image data using a flexible, high-dimensional uncertainty model. Based on this, a completely redesigned image processing pipeline is presented. In this pipeline, each step respects and preserves the underlying image uncertainty, allowing image uncertainty quantification, image pre-processing, image segmentation, and geometry extraction. This is communicated by utilizing meaningful visualization methodologies throughout each computational step. The presented methods are examined qualitatively by comparing to the Stateof- the-Art, in addition to user evaluation in different domains. To show the applicability of the presented approach to real world scenarios, this thesis demonstrates domain-specific problems and the successful implementation of the presented techniques in these domains.

The gas phase infrared and fragmentation spectra of a systematic group of trimetallic oxo-centered transition metal complexes are shown and discussed, with formate and acetate bridging ligands and pyridine and water as axial ligands. The stability of the complexes, as predicted by appropriate ab initio simulations, is demonstrated to agree with collision induced dissociation (CID) measurements. A broad range of DFT calculations are shown. They are used to simulate the geometry, the bonding situation, relative stability and flexibility of the discussed complexes, and to specify the observed trends. These simulations correctly predict the trends in the band splitting of the symmetric and asymmetric carboxylate stretch modes, but fail to account for anharmonic effects observed specifically in the mid IR range. The infrared spectra of the different ligands are introduced in a brief literature review. Their changes in different environments or different bonding situations are discussed and visualized, especially the interplay between fundamental-, overtone-, and combination bands, as well as Fermi resonances between them. A new variation on the infrared multi photon dissociation (IRMPD) spectroscopy method is proposed and evaluated. In addition to the commonly considered total fragment yield, the cumulative fragment yield can be used to plot the wavelength dependent relative abundance of different fragmentation products. This is shown to include valuable additional information on the excited chromophors, and their coupling to specific fragmentation channels. High quality homo- and heterometallic IRMPD spectra of oxo centered carboxylate complexes of chromium and iron show the impacts of the influencing factors: the metal centers, the bridging ligands, their carboxylate stretch modes and CH bend modes, and the terminal ligands. In all four formate spectra, anharmonic effects are necessary to explain the observed spectra: combination bands of both carboxylate stretch modes and a Fermi resonance of the fundamental of the CH stretch mode, and a combination band of the asymmetric carboxylate stretch mode with the CH bend mode of the formate bridging ligand. For the water adduct species, partial hydrolysis is proposed to account for the changes in the observed carboxylic stretch modes. Appropriate experiments are suggested to verify the mode assignments that are not directly explained by the ab initio calculations, the available experimental results or other means like deuteration experiments.

Numerical Godeaux surfaces are minimal surfaces of general type with the smallest possible numerical invariants. It is known that the torsion group of a numerical Godeaux surface is cyclic of order \(m\leq 5\). A full classification has been given for the cases \(m=3,4,5\) by the work of Reid and Miyaoka. In each case, the corresponding moduli space is 8-dimensional and irreducible. There exist explicit examples of numerical Godeaux surfaces for the orders \(m=1,2\), but a complete classification for these surfaces is still missing. In this thesis we present a construction method for numerical Godeaux surfaces which is based on homological algebra and computer algebra and which arises from an experimental approach by Schreyer. The main idea is to consider the canonical ring \(R(X)\) of a numerical Godeaux surface \(X\) as a module over some graded polynomial ring \(S\). The ring \(S\) is chosen so that \(R(X)\) is finitely generated as an \(S\)-module and a Gorenstein \(S\)-algebra of codimension 3. We prove that the canonical ring of any numerical Godeaux surface, considered as an \(S\)-module, admits a minimal free resolution whose middle map is alternating. Moreover, we show that a partial converse of this statement is true under some additional conditions. Afterwards we use these results to construct (canonical rings of) numerical Godeaux surfaces. Hereby, we restrict our study to surfaces whose bicanonical system has no fixed component but 4 distinct base points, in the following referred to as marked numerical Godeaux surfaces. The particular interest of this thesis lies on marked numerical Godeaux surfaces whose torsion group is trivial. For these surfaces we study the fibration of genus 4 over \(\mathbb{P}^1\) induced by the bicanonical system. Catanese and Pignatelli showed that the general fibre is non-hyperelliptic and that the number \(\tilde{h}\) of hyperelliptic fibres is bounded by 3. The two explicit constructions of numerical Godeaux surfaces with a trivial torsion group due to Barlow and Craighero-Gattazzo, respectively, satisfy \(\tilde{h} = 2\). With the method from this thesis, we construct an 8-dimensional family of numerical Godeaux surfaces with a trivial torsion group and whose general element satisfy \(\tilde{h}=0\). Furthermore, we establish a criterion for the existence of hyperelliptic fibres in terms of a minimal free resolution of \(R(X)\). Using this criterion, we verify experimentally the existence of a numerical Godeaux surface with \(\tilde{h}=1\).

The Symbol Grounding Problem (SGP) is one of the first attempts to proposed a hypothesis about mapping abstract concepts and the real world. For example, the concept "ball" can be represented by an object with a round shape (visual modality) and phonemes /b/ /a/ /l/ (audio modality). This thesis is inspired by the association learning presented in infant development. Newborns can associate visual and audio modalities of the same concept that are presented at the same time for vocabulary acquisition task. The goal of this thesis is to develop a novel framework that combines the constraints of the Symbol Grounding Problem and Neural Networks in a simplified scenario of association learning in infants. The first motivation is that the network output can be considered as numerical symbolic features because the attributes of input samples are already embedded. The second motivation is the association between two samples is predefined before training via the same vectorial representation. This thesis proposes to associate two samples and the vectorial representation during training. Two scenarios are considered: sample pair association and sequence pair association. Three main contributions are presented in this work. The first contribution is a novel Symbolic Association Model based on two parallel MLPs. The association task is defined by learning that two instances that represent one concept. Moreover, a novel training algorithm is defined by matching the output vectors of the MLPs with a statistical distribution for obtaining the relationship between concepts and vectorial representations. The second contribution is a novel Symbolic Association Model based on two parallel LSTM networks that are trained on weakly labeled sequences. The definition of association task is extended to learn that two sequences represent the same series of concepts. This model uses a training algorithm that is similar to MLP-based approach. The last contribution is a Classless Association. The association task is defined by learning based on the relationship of two samples that represents the same unknown concept. In summary, the contributions of this thesis are to extend Artificial Intelligence and Cognitive Computation research with a new constraint that is cognitive motivated. Moreover, two training algorithms with a new constraint are proposed for two cases: single and sequence associations. Besides, a new training rule with no-labels with promising results is proposed.

Though environmental inequality research has gained extensive interest in the United States, it has received far less attention in Europe and Germany. The main objective of this book is to extend the research on environmental inequality in Germany. This book aims to shed more light on the question of whether minorities in Germany are affected by a disproportionately high burden of environmental pollution, and to increase the general knowledge about the causal mechanisms, which contribute to the unequal distribution of environmental hazards across the population. To improve our knowledge about environmental inequality in Germany, this book extends previous research in several ways. First, to evaluate the extent of environmental inequality, this book relies on two different data sources. On the on hand, it uses household-level survey data and self-reports about the impairment through air pollution. On the other hand, it combines aggregated census data and objective register-based measures of industrial air pollution by using geographic information systems (GIS). Consequently, this book offers the first analysis of environmental inequality on the national level that uses objective measures of air pollution in Germany. Second, to evaluate the causes of environmental inequality, this book applies a panel data analysis on the household level, thereby offering the first longitudinal analysis of selective migration processes outside the United States. Third, it compares the level of environmental inequality between German metropolitan areas and evaluates to which extent the theoretical arguments of environmental inequality can explain differing levels of environmental inequality across the country. By doing so, this book not only investigates the impact of indicators derived by the standard strand of theoretical reasoning but also includes structural characteristics of the urban space. All studies presented in this book confirm the disproportionate exposure of minorities to environmental pollution. Minorities live in more polluted areas in Germany but also in more polluted parts of the communities, and this disadvantage is most severe in metropolitan regions. Though this book finds evidence for selective migration processes contributing to the disproportionate exposure of minorities to environmental pollution, it also stresses the importance of urban conditions. Especially cities with centrally located industrial facilities yield a high level of environmental inequality. This poses the question of whether environmental inequality might be the result of two independent processes: 1) urban infrastructure confines residential choices of minorities to the urban core, and 2) urban infrastructure facilitates centrally located industries. In combination, both processes lead to a disproportionate burden of minority households.

Computational problems that involve dynamic data, such as physics simulations and program development environments, have been an important subject of study in programming languages. Recent advances in self-adjusting computation made progress towards achieving efficient incremental computation by providing algorithmic language abstractions to express computations that respond automatically to dynamic changes in their inputs. Selfadjusting programs have been shown to be efficient for a broad range of problems via an explicit programming style, where the programmer uses specific primitives to identify, create and operate on data that can change over time. This dissertation presents implicit self-adjusting computation, a type directed technique for translating purely functional programs into self-adjusting programs. In this implicit approach, the programmer annotates the (toplevel) input types of the programs to be translated. Type inference finds all other types, and a type-directed translation rewrites the source program into an explicitly self-adjusting target program. The type system is related to information-flow type systems and enjoys decidable type inference via constraint solving. We prove that the translation outputs well-typed self-adjusting programs and preserves the source program’s input-output behavior, guaranteeing that translated programs respond correctly to all changes to their data. Using a cost semantics, we also prove that the translation preserves the asymptotic complexity of the source program. As a second contribution, we present two techniques to facilitate the processing of large and dynamic data in self-adjusting computation. First, we present a type system for precise dependency tracking that minimizes the time and space for storing dependency metadata. The type system improves the scalability of self-adjusting computation by eliminating an important assumption of prior work that can lead to recording spurious dependencies. We present a type-directed translation algorithm that generates correct selfadjusting programs without relying on this assumption. Second, we show a probabilistic-chunking technique to further decrease space usage by controlling the fundamental space-time tradeoff in self-adjusting computation. We implement implicit self-adjusting computation as an extension to Standard ML with compiler and runtime support. Using the compiler, we are able to incrementalize an interesting set of applications, including standard list and matrix benchmarks, ray tracer, PageRank, sparse graph connectivity, and social circle counts. Our experiments show that our compiler incrementalizes existing code with only trivial amounts of annotation, and the resulting programs bring asymptotic improvements to large datasets from real-world applications, leading to orders of magnitude speedups in practice.

This thesis consists of five chapters. Chapter one elaborates on the principle of cognitive consistency and provides an overview of what extant research refers to as cognitive consistency theories (e.g., Abelson et al., 1968; Harmon-Jones & Harmon-Jones, 2007; Simon, Stenstrom, & Read, 2015). Moreover, it describes the most prominent theoretical representatives in this context, namely balance theory (Heider, 1946, 1958), congruity theory (Osgood & Tannenbaum, 1955), and cognitive dissonance theory (Festinger, 1957). Chapter one further outlines the role of individuals’ preference for cognitive consistency in the context of financial resource acquisition, the recruitment of employees and the acquisition of customers in the entrepreneurial context. Chapter two is co-authored by Prof. Dr. Matthias Baum and presents two separate studies in which we empirically investigate the hypothesis that social entrepreneurs face a systematic disadvantage, compared to for-profit entrepreneurs, when seeking to acquire financial resources. Further, our work goes beyond existing research by introducing biased perceptions as a factor that may constrain social enterprise resource acquisition and therefore possibly stall the process of social value creation. On the foundation of role congruity theory (Eagly & Karau, 2002), we emphasize on the question whether social entrepreneurs provide signals which are less congruent with the stereotype of successful entrepreneurs and, in such, are perceived as less competent. We further test whether such biased competency perceptions feed forward into a lower probability to receive funding. Chapter three is also co-authored by Prof. Dr. Matthias Baum as well as by Eva Henrich. The aim of this chapter is to further our understanding of the early recruitment phase and to contribute to the current debate about how firms should orchestrate their recruitment channels in order to enhance the creation of employer knowledge. We introduce the concept of integrated marketing communication into the recruitment field and examine how the level of consistency regarding job or organization information affects the recall and the recognition of that information. We additionally test whether information consistency among multiple recruitment channels influences information recognition failure quota. Answering this question is important as by failing to remember the source of recruitment information, job seekers may attribute job information to the wrong firm and thus create an incorrect employer knowledge. Chapter four, which is co-authored by Prof. Dr. Matthias Baum, introduces customer congruity perceptions between a brand and a reward in the context of customer referral programs as an essential driver of the effectiveness of such programs. More precisely, we posit and empirically test a model according to which the decision-making process of the customer recommending a firm involves multiple mental steps and assumes reward perceptions to be an immediate antecedent of brand evaluation, which then, ultimately shapes the likelihood of recommendation. The level of congruity/incongruity is set up as an antecedent state and affects the perceived attractiveness of the reward. Our work contributes to the discussion on the optimal level of congruity between a prevailing schema in the mind of the customer and a stimulus presented. In addition, chapter four introduces customer referral programs as a strategic tool for brand managers. Chapter four is further published in Psychology & Marketing. Chapter five first proposes that marketing strategies specifically designed to induce word-of-mouth (WOM) behavior are particular relevant for new ventures. Against the background that previous research suggests that customer perceptions of young firm age may influence customer behavior and the degree to which customers support new ventures (e.g., Choi & Shepherd, 2005; Stinchcombe, 1965), we secondly conduct an experiment to examine the causal mechanisms linking firm age and customer WOM. Chapter five, too, is co-authored by Prof. Dr. Matthias Baum.

Road accidents remain as one of the major causes of death and injuries globally. Several million people die every year due to road accidents all over the world. Although the number of accidents in European region have reduced in the past years, road safety still remains a major challenge. Especially in case of commercial trucks, due to the size and load of the vehicle, even minor collisions with other road users would lead to serious injuries or death. In order to reduce number of accidents, automotive industry is rapidly developing advanced driver assistance systems (ADAS) and automated driving technologies. Efficient and reliable solutions are required for these systems to sense, perceive and react to different environmental conditions. For vehicle safety applications such as collision avoidance with vulnerable road users (VRUs), it is not only important for the system to efficiently detect and track the objects in the vicinity of the vehicle but should also function robustly. An environment perception solution for application in commercial truck safety systems and for future automated driving is developed in this work. Thereby a method for integrated tracking and classification of road users in the near vicinity of the vehicle is formulated. The drawbacks in conventional multi-object tracking algorithms with respect to state, measurement and data association uncertainties have been addressed with the recent advancements in the field of unified multi-object tracking solutions based on random finite sets (RFS). Gaussian mixture implementation of the recently developed labeled multi-Bernoulli (LMB) filter [RSD15] is used as the basis for multi-object tracking in this work. Measurement from an high-resolution radar sensor is used as the main input for detecting and tracking objects. On one side, the focus of this work is on tracking VRUs in the near vicinity of the truck. As it is beneficial for most of the vehicle safety systems to also know the category that the object belongs to, the focus on the other side is also to classify the road users. All the radar detections believed to originate from a single object are clustered together with help of density based spatial clustering for application with noise (DBSCAN) algorithm. Each cluster of detections would have different properties based on the respective object characteristics. Sixteen distinct features based on radar detections, that are suitable for separating pedestrians, bicyclists and passenger car categories are selected and extracted for each of the cluster. A machine learning based classifier is constructed, trained and parameterised for distinguishing the road users based on the extracted features. The class information derived from the radar detections can further be used by the tracking algorithm, to adapt the model parameters used for precisely predicting the object motion according to the category of the object. Multiple model labeled multi-Bernoulli filter (MMLMB) is used for modelling different object motions. Apart from the detection level, the estimated state of an object on the tracking level also provides information about the object class. Both these informations are fused using Dempster-Shafer theory (DST) of evidence, based on respective class probabilities Thereby, the output of the integrated tracking and classification with MMLMB filter are classified tracks that can be used by truck safety applications with better reliability. The developed environment perception method is further implemented as a real-time prototypical system on a commercial truck. The performance of the tracking and classification approaches are evaluated with the help of simulation and multiple test scenarios. A comparison of the developed approaches to a conventional converted measurements Kalman filter with global nearest neighbour association (CMKF-GNN) shows significant advantages in the overall accuracy and performance.

This research explores the development of web based reference software for characterisation of surface roughness for two-dimensional surface data. The reference software used for verification of surface characteristics makes the evaluation methods easier for clients. The algorithms used in this software are based on International ISO standards. Most software used in industrial measuring instruments may give variations in the parameters calculated due to numerical changes in calculation. Such variations can be verified using the proposed reference software. The evaluation of surface roughness is carried out in four major steps: data capture, data align, data filtering and parameter calculation. This work walks through each of these steps explaining how surface profiles are evaluated by pre-processing steps called fitting and filtering. The analysis process is then followed by parameter evaluation according to DIN EN ISO 4287 and DIN EN ISO 13565-2 standards to extract important information from the profile to characterise surface roughness.

If gradient based derivative algorithms are used to improve industrial products by reducing their target functions, the derivatives need to be exact. The last percent of possible improvement, like the efficiency of a turbine, can only be gained if the derivatives are consistent with the solution process that is used in the simulation software. It is problematic that the development of the simulation software is an ongoing process which leads to the use of approximated derivatives. If a derivative computation is implemented manually, it will be inconsistent after some time if it is not updated. This thesis presents a generalized approach which differentiates the whole simulation software with Algorithmic Differentiation (AD), and guarantees a correct and consistent derivative computation after each change to the software. For this purpose, the variable tagging technique is developed. The technique checks at run-time if all dependencies, which are used by the derivative algorithms, are correct. Since it is also necessary to check the correctness of the implementation, a theorem is developed which describes how AD derivatives can be compared. This theorem is used to develop further methods that can detect and correct errors. All methods are designed such that they can be applied in real world applications and are used within industrial configurations. The process described above yields consistent and correct derivatives but the efficiency can still be improved. This is done by deriving new derivative algorithms. A fixed-point iterator approach, with a consistent derivation, yields all state of the art algorithms and produces two new algorithms. These two new algorithms include all implementation details and therefore they produce consistent derivative results. For detecting hot spots in the application, the state of the art techniques are presented and extended. The data management is changed such that the performance of the software is affected only marginally when quantities, like the number of input and output variables or the memory consumption, are computed for the detection. The hot spots can be treated with techniques like checkpointing or preaccumulation. How these techniques change the time and memory consumption is analyzed and it is shown how they need to be used in selected AD tools. As a last step, the used AD tools are analyzed in more detail. The major implementation strategies for operator overloading AD tools are presented and implementation improvements for existing AD tools are discussed.\ The discussion focuses on a minimal memory consumption and makes it possible to compare AD tools on a theoretical level. The new AD tool CoDiPack is based on these findings and its design and concepts are presented. The improvements and findings in this thesis make it possible, that an automatic, consistent and correct derivative is generated in an efficient way for industrial applications.

Fast Internet content delivery relies on two layers of caches on the request path. Firstly, content delivery networks (CDNs) seek to answer user requests before they traverse slow Internet paths. Secondly, aggregation caches in data centers seek to answer user requests before they traverse slow backend systems. The key challenge in managing these caches is the high variability of object sizes, request patterns, and retrieval latencies. Unfortunately, most existing literature focuses on caching with low (or no) variability in object sizes and ignores the intricacies of data center subsystems. This thesis seeks to fill this gap with three contributions. First, we design a new caching system, called AdaptSize, that is robust under high object size variability. Second, we derive a method (called Flow-Offline Optimum or FOO) to predict the optimal cache hit ratio under variable object sizes. Third, we design a new caching system, called RobinHood, that exploits variances in retrieval latencies to deliver faster responses to user requests in data centers. The techniques proposed in this thesis significantly improve the performance of CDN and data center caches. On two production traces from one of the world's largest CDN AdaptSize achieves 30-91% higher hit ratios than widely-used production systems, and 33-46% higher hit ratios than state-of-the-art research systems. Further, AdaptSize reduces the latency by more than 30% at the median, 90-percentile and 99-percentile. We evaluate the accuracy of our FOO analysis technique on eight different production traces spanning four major Internet companies. We find that FOO's error is at most 0.3%. Further, FOO reveals that the gap between online policies and OPT is much larger than previously thought: 27% on average, and up to 43% on web application traces. We evaluate RobinHood with production traces from a major Internet company on a 50-server cluster. We find that RobinHood improves the 99-percentile latency by more than 50% over existing caching systems. As load imbalances grow, RobinHood's latency improvement can be more than 2x. Further, we show that RobinHood is robust against server failures and adapts to automatic scaling of backend systems. The results of this thesis demonstrate the power of guiding the design of practical caching policies using mathematical performance models and analysis. These models are general enough to find application in other areas of caching design and future challenges in Internet content delivery.

In modern algebraic geometry solutions of polynomial equations are studied from a qualitative point of view using highly sophisticated tools such as cohomology, \(D\)-modules and Hodge structures. The latter have been unified in Saito’s far-reaching theory of mixed Hodge modules, that has shown striking applications including vanishing theorems for cohomology. A mixed Hodge module can be seen as a special type of filtered \(D\)-module, which is an algebraic counterpart of a system of linear differential equations. We present the first algorithmic approach to Saito’s theory. To this end, we develop a Gröbner basis theory for a new class of algebras generalizing PBW-algebras. The category of mixed Hodge modules satisfies Grothendieck’s six-functor formalism. In part these functors rely on an additional natural filtration, the so-called \(V\)-filtration. A key result of this thesis is an algorithm to compute the \(V\)-filtration in the filtered setting. We derive from this algorithm methods for the computation of (extraordinary) direct image functors under open embeddings of complements of pure codimension one subvarieties. As side results we show how to compute vanishing and nearby cycle functors and a quasi-inverse of Kashiwara’s equivalence for mixed Hodge modules. Describing these functors in terms of local coordinates and taking local sections, we reduce the corresponding computations to algorithms over certain bifiltered algebras. It leads us to introduce the class of so-called PBW-reduction-algebras, a generalization of the class of PBW-algebras. We establish a comprehensive Gröbner basis framework for this generalization representing the involved filtrations by weight vectors.

Certain brain tumours are very hard to treat with radiotherapy due to their irregular shape caused by the infiltrative nature of the tumour cells. To enhance the estimation of the tumour extent one may use a mathematical model. As the brain structure plays an important role for the cell migration, it has to be included in such a model. This is done via diffusion-MRI data. We set up a multiscale model class accounting among others for integrin-mediated movement of cancer cells in the brain tissue, and the integrin-mediated proliferation. Moreover, we model a novel chemotherapy in combination with standard radiotherapy. Thereby, we start on the cellular scale in order to describe migration. Then we deduce mean-field equations on the mesoscopic (cell density) scale on which we also incorporate cell proliferation. To reduce the phase space of the mesoscopic equation, we use parabolic scaling and deduce an effective description in the form of a reaction-convection-diffusion equation on the macroscopic spatio-temporal scale. On this scale we perform three dimensional numerical simulations for the tumour cell density, thereby incorporating real diffusion tensor imaging data. To this aim, we present programmes for the data processing taking the raw medical data and processing it to the form to be included in the numerical simulation. Thanks to the reduction of the phase space, the numerical simulations are fast enough to enable application in clinical practice.

The use of polymers subjected to various tribological situations has become state of the art. Owing to the advantages of self-lubrication and superior cleanliness, more and more polymer composites are now being used as sliding elements, which were formerly composed of metallic materials only. The feature that makes polymer composites so promising in industrial applications is the opportunity to tailor their properties with special fillers. The main aim of this study was to strength the importance of integrating various functional fillers in the design of wear-resistant polymer composites and to understand the role of fillers in modifying the wear behaviour of the materials. Special emphasis was focused on enhancement of the wear resistance of thermosetting and thermoplastic matrix composites by nano-TiO2 particles (with a diameter of 300nm). In order to optimize the content of various fillers, the tribological performance of a series of epoxy-based composites, filled with short carbon fibre (SCF), graphite, PTFE and nano-TiO2 in different proportions and combinations, was investigated. The patterns of frictional coefficient, wear resistance and contact temperature were examined by a pin-on-disc apparatus in a dry sliding condition under different contact pressures and sliding velocities. The experimental results indicated that the addition of nano-TiO2 effectively reduced the frictional coefficient, and consequently the contact temperature, of short-fibre reinforced epoxy composites. Based on scanning electron microscopy (SEM) and atomic force microscopy (AFM) observations of the worn surfaces, a positive rolling effect of the nanoparticles between the material pairs was proposed, which led to remarkable reduction of the frictional coefficient. In particular, this rolling effect protected the SCF from more severe wear mechanisms, especially in high sliding pressure and speed situations. As a result, the load carrying capacity of materials was significantly improved. In addition, the different contributions of two solid lubricants, PTFE powders and graphite flakes, on the tribological performance of epoxy nanocomposites were compared. It seems that graphite contributes to the improved wear resistance in general, whereas PTFE can easily form a transfer film and reduce the wear rate, especially in the running-in period. A combination of SCF and solid lubricants (PTFE and graphite) together with TiO2 nanoparticles can achieve a synergistic effect on the wear behaviour of materials. The favourable effect of nanoparticles detected in epoxy composites was also found in the investigations of thermoplastic, e.g. polyamide (PA) 6,6 matrix. It was found that nanoparticles could reduce the friction coefficient and wear rate of the PA6,6 composite remarkably, when additionally incorporated with short carbon fibres and graphite flakes. In particular, the addition of nanoparticles contributed to an obvious enhancement of the tribological performances of the short-fibre reinforced, hightemperature resistant polymers, e.g. polyetherimide (PEI), especially under extreme sliding conditions. A procedure was proposed in order to correlate the contact temperature and the wear rate with the frictional dissipated energy. Based on this energy consideration, a better interpretation of the different performance of distinct tribo-systems is possible. The validity of the model was illustrated for various sliding tests under different conditions. Although simple quantitative formulations could not be expected at present, the study may lead to a fundamental understanding of the mechanisms controlling friction and wear from a general system point of view. Moreover, using the energybased models, the artificial neural network (ANN) approach was applied to the experimental data. The well-trained ANN has the potential to be further used for online monitoring and prediction of wear progress in practical applications. Die Verwendung von Polymeren im Hinblick auf verschiedene tribologische Anwendungen entspricht mittlerweile dem Stand der Technik. Aufgrund der Vorteile von Selbstschmierung und ausgezeichneter Sauberkeit werden polymere Verbundwerkstoffe immer mehr als Gleitelemente genutzt, welche früher ausschließlich aus metallischen Werkstoffen bestanden. Die Besonderheit, die polymere Verbundwerkstoffe so vielversprechend für industrielle Anwendungen macht, ist die Möglichkeit ihre Eigenschaften durch Zugabe von speziellen Füllstoffen maßzuschneidern. Das Hauptziel dieser Arbeit bestand darin, die Wichtigkeit der Integration verschiedener funktionalisierter Füllstoffe in den Aufbau polymerer Verbundwerkstoffe mit hohem Verschleißwiderstand aufzuzeigen und die Rolle der Füllstoffe hinsichtlich des Verschleißverhaltens zu verstehen. Hierbei lag besonderes Augenmerk auf der Verbesserung des Verschleißwiderstandes bei Verbunden mit duromerer und thermoplastischer Matrix durch die Präsenz von TiO2-Partikeln (Durchmesser 300nm). Das tribologische Verhalten epoxidharzbasierter Verbunde, gefüllt mit kurzen Kohlenstofffasern (SCF), Graphite, PTFE und nano-TiO2 in unterschiedlichen Proportionen und Kombinationen wurde untersucht, um den jeweiligen Füllstoffgehalt zu optimieren. Das Verhalten von Reibungskoeffizient, Verschleißwiderstand und Kontakttemperatur wurde unter Verwendung einer Stift-Scheibe Apparatur bei trockenem Gleitzustand, verschiedenen Kontaktdrücken und Gleitgeschwindigkeiten erforscht. Die experimentellen Ergebnisse zeigen, dass die Zugabe von nano-TiO2 in kohlenstofffaserverstärkte Epoxide den Reibungskoeffizienten und die Kontakttemperatur herabsetzen können. Basierend auf Aufnahmen der verschlissenen Oberflächen durch Rasterelektronen- (REM) und Rasterkraftmikroskopie (AFM) trat ein positiver Rolleffekt der Nanopartikel zwischen den Materialpaaren zum Vorschein, welcher zu einer beachtlichen Reduktion des Reibungskoeffizienten führte. Dieser Rolleffekt schützte insbesondere die SCF vor schwerwiegenderen Verschleißmechanismen, speziell bei hohem Gleitdruck und hohen Geschwindigkeiten. Als Ergebnis konnte die Tragfähigkeit dieser Materialien wesentlich verbessert werden. Zusätzlich wurde die Wirkung zweier fester Schmierstoffe (PTFE-Pulver und Graphit-Flocken) auf die tribologische Leistungsfähigkeit verglichen. Es scheint, daß Graphit generell zur Verbesserung des Verschleißwiderstandes beiträgt, wobei PTFE einen Transferfilm bilden kann und die Verschleißrate insbesondere in der Einlaufphase reduziert. Die Kombination von SCF und festen Schmierstoffen zusammen mit TiO2-Nanopartikeln kann einen Synergieeffekt bei dem Verschleißverhalten der Materialien hervorrufen. Der positive Effekt der Nanopartikel in Duromeren wurde ebenfalls bei den Untersuchungen von Thermoplasten (PA 66) gefunden. Die Nanopartikel konnten den Reibungskoeffizienten und die Verschleißrate der PA 66-Verbunde herabsetzen, wobei zusätzlich Kohlenstofffasern und Graphit-Flocken enthalten waren. Die Zugabe von Nanopartikeln trug offensichtlich auch zur Verbesserung der tribologischen Leistungsfähigkeit von SCF-verstärkten, hochtemperaturbeständigen Polymeren (PEI) insbesondere unter extremen Gleitzuständen, bei. Es wurde eine Methode vorgestellt, um die Kontakttemperatur und die Verschleißrate mit der durch Reibung dissipierten Energie zu korrelieren. Diese Energiebetrachtung ermöglicht eine bessere Interpretation der verschiedenen Eigenschaften von ausgewählten Tribo-Systemen. Die Gültigkeit dieses Models wurde für mehrere Gleittests unter verschiedenen Bedingungen erklärt. Vom generellen Blickpunkt eines tribologischen Systems aus mag diese Arbeit zu einem fundamentalen Verständnis der Mechanismen führen, welche das Reibungs und Verschleißverhalten kontrollieren, obwohl hier einfache quantitative (mathematische) Zusammenhänge bisher nicht zu erwarten sind. Der auf energiebasierenden Modellen fußende Lösungsansatz der neuronalen Netzwerke (ANN) wurde darüber hinaus auf die experimentellen Datensätze angewendet. Die gut trainierten ANN's besitzen das Potenzial sie in der praktischen Anwendungen zur Online- Datenauswertung und zur Vorhersage des Verschleißfortschritts einzusetzen.

Fucoidan is a class of biopolymers mainly found in brown seaweeds. Due to its diverse medical importance, homogenous supply as well as a GMP-compliant product is of a special interest. Therefore, in addition to optimization of its extraction and purification from classical resources, other techniques were tried (e.g., marine tissue culture and heterologous expression of enzymes involved in its biosynthesis). Results showed that 17.5% (w/w) crude fucoidan after pre-treatment and extraction was obtained from the brown macroalgae F. vesiculosus. Purification by affinity chromatography improved purity relative to the commercial purified product. Furthermore, biological investigations revealed improved anti-coagulant and anti-viral activities compared with crude fucoidan. Furthermore, callus-like and protoplast cultures as well as bioreactor cultivation were developed from F. vesiculosus representing a new horizon to produce fucoidan biotechnologically. Moreover, heterologous expression of several enzymes involved in its biosynthesis by E. coli (e.g., FucTs and STs) demonstrated the possibility to obtain active enzymes that could be utilized in enzymatic in vitro synthesis of fucoidan. All these competitive techniques could provide the global demands from fucoidan.

The phase field approach is a powerful tool that can handle even complicated fracture phenomena within an apparently simple framework. Nonetheless, a profound understanding of the model is required in order to be able to interpret the obtained results correctly. Furthermore, in the dynamic case the phase field model needs to be verified in comparison to experimental data and analytical results in order to increase the trust in this new approach. In this thesis, a phase field model for dynamic brittle fracture is investigated with regard to these aspects by analytical and numerical methods

Asynchronous concurrency is a wide-spread way of writing programs that deal with many short tasks. It is the programming model behind event-driven concurrency, as exemplified by GUI applications, where the tasks correspond to event handlers, web applications based around JavaScript, the implementation of web browsers, but also of server-side software or operating systems. This model is widely used because it provides the performance benefits of concurrency together with easier programming than multi-threading. While there is ample work on how to implement asynchronous programs, and significant work on testing and model checking, little research has been done on handling asynchronous programs that involve heap manipulation, nor on how to automatically optimize code for asynchronous concurrency. This thesis addresses the question of how we can reason about asynchronous programs while considering the heap, and how to use this this to optimize programs. The work is organized along the main questions: (i) How can we reason about asynchronous programs, without ignoring the heap? (ii) How can we use such reasoning techniques to optimize programs involving asynchronous behavior? (iii) How can we transfer these reasoning and optimization techniques to other settings? The unifying idea behind all the results in the thesis is the use of an appropriate model encompassing global state and a promise-based model of asynchronous concurrency. For the first question, We start from refinement type systems for sequential programs and extend them to perform precise resource-based reasoning in terms of heap contents, known outstanding tasks and promises. This extended type system is known as Asynchronous Liquid Separation Types, or ALST for short. We implement ALST in for OCaml programs using the Lwt library. For the second question, we consider a family of possible program optimizations, described by a set of rewriting rules, the DWFM rules. The rewriting rules are type-driven: We only guarantee soundness for programs that are well-typed under ALST. We give a soundness proof based on a semantic interpretation of ALST that allows us to show behavior inclusion of pairs of programs. For the third question, we address an optimization problem from industrial practice: Normally, JavaScript files that are referenced in an HTML file are be loaded synchronously, i.e., when a script tag is encountered, the browser must suspend parsing, then load and execute the script, and only after will it continue parsing HTML. But in practice, there are numerous JavaScript files for which asynchronous loading would be perfectly sound. First, we sketch a hypothetical optimization using the DWFM rules and a static analysis. To actually implement the analysis, we modify the approach to use a dynamic analysis. This analysis, known as JSDefer, enables us to analyze real-world web pages, and provide experimental evidence for the efficiency of this transformation.

The N-containing heterocycles have received strong attention from the organic synthesis field because of their importance for pharmaceutical and material sciences. Nitrogen element plays an important role between inorganic salts and biomolecules, to search convenient methods combine C-N bond together become a hot topic in recent decades. Since the early beginning of 20th century, transition-metal-catalyzed coupling reactions had been well-known and world widely spread in organic researchs, achieved abundant significant progress. In the other side, the less toxic and more challenging transition metal free coupling method remained further potential value. With the evolution of amination reactions and oxidants, more and more effective, simplified, and atom economic organic synthesis methods will come soon. And these stories also drove me to think about investigating the novel cross-dehydrogenative-coupling amination methods development as the topics of my PhD research. Thus, we selected the phenothiazine derivatives as the N-nucleophile reagents and the phenols as the C-nucleophile reagents. To achieve the transition metal-free CDC aminations of phenols with phenothiazines, we scanned the chemical toolbox and tested a series of both common and uncommon oxidants. Firstly, we start the condition in the presence of cumene and O2. The proposed mechanism initiated by a Hock process, which would form in situ peroxo-species as initiator of the reaction. And the initial infra-red analysis predicted there is a strong O-H..N interaction. In the second method, a series of iodines with different valance have been tested to achieve the C-N bond formation of phenols with phenothiazines. This time, a simplified and more efficient method had been developed, which also provides a wider scope of phenols. Several controlling experiments had been conducted for the plausible pathway research. Large-scale synthesis of target molecular was also successfully performed. And then, we focus the research on the cross-coupling reaction of pre-oxidized(iminated) phenothiazine with ubiquitous phenols and indoles. In this task, we first regio-selectively synthesized the novel iminated phenothiazine derivatives with the traditional biocide and mild disinfectant, Chloramine T. Then the phenothiazinimine performed an ultra-simple condensation technique with phenol or indole coupling partners in a simplified condition. Parallel reactions were also performed to investigate the plausible pathway.

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.

Due to the steadily growing flood of data, the appropriate use of visualizations for efficient data analysis is as important today as it has never been before. In many application domains, the data flood is based on processes that can be represented by node-link diagrams. Within such a diagram, nodes may represent intermediate results (or products), system states (or snapshots), milestones or real (and possibly georeferenced) objects, while links (edges) can embody transition conditions, transformation processes or real physical connections. Inspired by the engineering sciences application domain and the research project “SinOptiKom: Cross-sectoral optimization of transformation processes in municipal infrastructures in rural areas”, a platform for the analysis of transformation processes has been researched and developed based on a geographic information system (GIS). Caused by the increased amount of available and interesting data, a particular challenge is the simultaneous visualization of several visible attributes within one single diagram instead of using multiple ones. Therefore, two approaches have been developed, which utilize the available space between nodes in a diagram to display additional information. Motivated by the necessity of appropriate result communication with various stakeholders, a concept for a universal, dashboard-based analysis platform has been developed. This web-based approach is conceptually capable of displaying data from various data sources and has been supplemented by collaboration possibilities such as sharing, annotating and presenting features. In order to demonstrate the applicability and usability of newly developed applications, visualizations or user interfaces, extensive evaluations with human users are often inevitable. To reduce the complexity and the effort for conducting an evaluation, the browser-based evaluation framework (BREF) has been designed and implemented. Through its universal and flexible character, virtually any visualization or interaction running in the browser can be evaluated with BREF without any additional application (except for a modern web browser) on the target device. BREF has already proved itself in a wide range of application areas during the development and has since grown into a comprehensive evaluation tool.

In this thesis we integrate discrete dividends into the stock model, estimate future outstanding dividend payments and solve different portfolio optimization problems. Therefore, we discuss three well-known stock models, including discrete dividend payments and evolve a model, which also takes early announcement into account. In order to estimate the future outstanding dividend payments, we develop a general estimation framework. First, we investigate a model-free, no-arbitrage methodology, which is based on the put-call parity for European options. Our approach integrates all available option market data and simultaneously calculates the market-implied discount curve. We illustrate our method using stocks of European blue-chip companies and show within a statistical assessment that the estimate performs well in practice. As American options are more common, we additionally develop a methodology, which is based on market prices of American at-the-money options. This method relies on a linear combination of no-arbitrage bounds of the dividends, where the corresponding optimal weight is determined via a historical least squares estimation using realized dividends. We demonstrate our method using all Dow Jones Industrial Average constituents and provide a robustness check with respect to the used discount factor. Furthermore, we backtest our results against the method using European options and against a so called simple estimate. In the last part of the thesis we solve the terminal wealth portfolio optimization problem for a dividend paying stock. In the case of the logarithmic utility function, we show that the optimal strategy is not a constant anymore but connected to the Merton strategy. Additionally, we solve a special optimal consumption problem, where the investor is only allowed to consume dividends. We show that this problem can be reduced to the before solved terminal wealth problem.

European economic, social and territorial cohesion is one of the fundamental aims of the European Union (EU). It seeks to both reduce the effects of internal borders and enhance European integration. In order to facilitate territorial cohesion, the linkage of member states by means of efficient cross-border transport infrastructures and services is an important factor. Many cross-border transport challenges have historically existed in everyday life. They have hampered smooth passenger and freight flows within the EU. Two EU policies, namely European Territorial Cooperation (ETC) and the Trans-European Transport Networks (TEN-T), promote enhancing cross-border transport through cooperation in soft spaces. This dissertation seeks to explore the influence of these two EU policies on cross-border transport and further European integration. Based on an analysis of European, national and cross-border policy and planning documents, surveys with TEN-T Corridor Coordinators and INTERREG Secretariats and a high number of elite interviews, the dissertation will investigate how the objectives of the two EU policies were formally implemented in both soft spaces and the EU member states as well as which practical implementations have taken place. Thereby, the initiated Europeanisation and European integration processes will be evaluated. The analysis is conducted in nine preliminary case studies and two in-depth case studies. The cases comprise cross-border regions funded by the ETC policy that are crossed by a TEN-T corridor. The in-depth analysis explores the Greater Region Saar-Lor-Lux+ and the Brandenburg-Lubuskie region. The cases are characterised by different initial situations. The research determined that the two EU policies support cross-border transport on different levels and, further, that they need to be better intertwined in order to make effective use of their complementarities. Moreover, it became clear that the EU policies have a distinct influence on domestic policy and planning documents of different administrative levels and countries as well as on the practical implementation. The final implementation of the EU objectives and the cross-border transport initiatives was strongly influenced by the member states’ initial situations – particularly, the regional and local transport needs. This dissertation concludes that the two EU policies cannot remove the entirety of the cross-border transport-related challenges. However, in addition to their financial investments in concrete projects, they promote the importance of cross-border transport and facilitate cooperation, learning and exchange processes. These are all of high relevance to cross-border transport development, driven by member states, as well as to further European integration. The dissertation recommends that the transport planning competences of the EU in addition to the TEN-T network should not be enlarged in the future, but rather further transnational transport development tasks should be decentralised to transnational transport planning committees that are aware of regional needs and can coordinate a joint transport development strategy. The latter should be implemented with the support of additional EU funds for secondary and tertiary cross-border connections. Moreover, the potential complementarities of the transnational regions and transport corridors as well as the two EU policy fields should be made better use of by improving communication. This means that soft spaces, the TEN-T and ETC Policy as well as the domestic transport ministries and the domestic administrations that are responsible for the two EU policies need to intensify their cooperation. Furthermore, a focus of future ETC projects on topics that are of added value for the whole cross-border region or else that can be applied in different territorial contexts is recommended rather than investing in small-scale scattered expensive infrastructures and services that are only of benefit for a small part of the region. Additionally, the dissemination of project results should be enhanced so that the developed tools can be accessed by potential users and benefits become more visible to a wider society, despite the fact that they might not be measurable in numbers. In addition, the research points at another success factor for more concrete outputs: the frequent involvement of transport and spatial planners in transnational projects could increase the relation to planning practice. Besides that, advanced training regarding planning culture could reduce cooperation barriers.

The research problem is that the land-use (re-)planning process in the existing Egyptian cities does not attain sustainability. This is because of the unfulfillment of essential principles within their land-use structures, lack of harmony between the added and old parts in the cities, and other reasons. This leads to the need for developing an assessment system, which is a computational spatial planning support system-SPSS. This SPSS is used for identifying the degree of sustainability attainment in land-uses plans, predicting probable problems, and suggesting modifications in the evaluated plans. The main goal is to design the SPSS for supporting sustainability in the Egyptian cities. The secondary goals are: studying the Egyptian planning and administrative systems for designing the technical and administrative frameworks for the SPSS, the development of an assessment model from the SPSS for assessing sustainability in land-use structures of urban areas, as well as the identification of the improvements required in the model and the recommendations for developing the SPSS. The theoretical part aims to design each of the administrative and technical frameworks of the SPSS. This requires studying each of the main planning approaches, the sustainability in urban land-use planning, and the significance of using efficient assessment tools for evaluating the sustainability in this process. The added value of the planning support systems-PSSs for planning and their role in supporting sustainability attainment in urban land-use planning are discussed. Then, a group of previous examples in the sustainability assessment from various countries (developed and developing countries) are selected, which have used various assessment tools. This is to extract some learned lessons to be guides for the SPSS. And so, the comprehensive technical framework for the SPSS is designed, which includes the suggested methods and techniques that perform various stages of the assessment process. The Egyptian context is studied regarding the planning and administration systems within the Egyptian cities, as well as the spatial and administrative problems facing the sustainable development. And so, the administrative framework for the SPSS is identified, which includes the entities that should be involved in the assessment process. The empirical part focuses on the design of a selected assessment model from the comprehensive technical framework of the SPSS to be established as a minimized version from it. This model is programmed in the form of a new toolbox within the ArcGIS™ software through geoscripting using Python programming language to be applied for assessing the sustainability attainment in the land-use structure of urban areas. The required assessing criteria for the model specialized for the Egyptian and German cities are identified, for applying it on German and Egyptian study areas. The conclusions regarding each of PSSs, the Egyptian local administration and planning systems, sustainability attainment in the land-use planning process in Egyptian Cities, as well as the proposed SPSS and the developed toolbox are drawn. The recommendations are regarding each of challenges facing the development and application of PSSs, the Egyptian local administration and planning systems, the spatial problems in Egyptian cities, the establishment of the SPSS, and the application of the toolbox. The future agenda is in the fields of sustainable urban land-use planning, planning support science, and the development process in the Egyptian cities.

In this thesis, we focus on the application of the Heath-Platen (HP) estimator in option pricing. In particular, we extend the approach of the HP estimator for pricing path dependent options under the Heston model. The theoretical background of the estimator was first introduced by Heath and Platen [32]. The HP estimator was originally interpreted as a control variate technique and an application for European vanilla options was presented in [32]. For European vanilla options, the HP estimator provided a considerable amount of variance reduction. Thus, applying the technique for path dependent options under the Heston model is the main contribution of this thesis. The first part of the thesis deals with the implementation of the HP estimator for pricing one-sided knockout barrier options. The main difficulty for the implementation of the HP estimator is located in the determination of the first hitting time of the barrier. To test the efficiency of the HP estimator we conduct numerical tests with regard to various aspects. We provide a comparison among the crude Monte Carlo estimation, the crude control variate technique and the HP estimator for all types of barrier options. Furthermore, we present the numerical results for at the money, in the money and out of the money barrier options. As numerical results imply, the HP estimator performs superior among others for pricing one-sided knockout barrier options under the Heston model. Another contribution of this thesis is the application of the HP estimator in pricing bond options under the Cox-Ingersoll-Ross (CIR) model and the Fong-Vasicek (FV) model. As suggested in the original paper of Heath and Platen [32], the HP estimator has a wide range of applicability for derivative pricing. Therefore, transferring the structure of the HP estimator for pricing bond options is a promising contribution. As the approximating Vasicek process does not seem to be as good as the deterministic volatility process in the Heston setting, the performance of the HP estimator in the CIR model is only relatively good. However, for the FV model the variance reduction provided by the HP estimator is again considerable. Finally, the numerical result concerning the weak convergence rate of the HP estimator for pricing European vanilla options in the Heston model is presented. As supported by numerical analysis, the HP estimator has weak convergence of order almost 1.

1,3-Diynes are frequently found as an important structural motif in natural products, pharmaceuticals and bioactive compounds, electronic and optical materials and supramolecular molecules. Copper and palladium complexes are widely used to prepare 1,3-diynes by homocoupling of terminal alkynes; albeit the potential of nickel complexes towards the same is essentially unexplored. Although a detailed study on the reported nickel-acetylene chemistry has not been carried out, a generalized mechanism featuring a nickel(II)/nickel(0) catalytic cycle has been proposed. In the present work, a detailed mechanistic aspect of the nickel-mediated homocoupling reaction of terminal alkynes is investigated through the isolation and/or characterization of key intermediates from both the stoichiometric and the catalytic reactions. A nickel(II) complex [Ni(L-N4Me2)(MeCN)2](ClO4)2 (1) containing a tetradentate N,N′-dimethyl-2,11-diaza[3.3](2,6)pyridinophane (L-N4Me2) as ligand was used as catalyst for homocoupling of terminal alkynes by employing oxygen as oxidant at room temperature. A series of dinuclear nickel(I) complexes bridged by a 1,3-diyne ligand have been isolated from stoichiometric reaction between [Ni(L-N4Me2)(MeCN)2](ClO4)2 (1) and lithium acetylides. The dinuclear nickel(I)-diyne complexes [{Ni(L-N4Me2)}2(RC4R)](ClO4)2 (2) were well characterized by X-ray crystal structures, various spectroscopic methods, SQUID and DFT calculation. The complexes not only represent as a key intermediate in aforesaid catalytic reaction, but also describe the first structurally characterized dinuclear nickel(I)-diyne complexes. In addition, radical trapping and low temperature UV-Vis-NIR experiments in the formation of the dinuclear nickel(I)-diyne confirm that the reactions occurring during the reduction of nickel(II) to nickel(I) and C-C bond formation of 1,3-diyne follow non-radical concerted mechanism. Furthermore, spectroscopic investigation on the reactivity of the dinuclear nickel(I)-diyne complex towards molecular oxygen confirmed the formation of a mononuclear nickel(I)-diyne species [Ni(L-N4Me2)(RC4R)]+ (4) and a mononuclear nickel(III)-peroxo species [Ni(L-N4Me2)(O2)]+ (5) which were converted to free 1,3-diyne and an unstable dinuclear nickel(II) species [{Ni(L-N4Me2)}2(O2)]2+ (6). A mononuclear nickel(I)-alkyne complex [Ni(L-N4Me2)(PhC2Ph)](ClO4).MeOH (3) and the mononuclear nickel(III)-peroxo species [Ni(L-N4Me2)(O2)]+ (5) were isolated/generated and characterized to confirm the formulation of aforementioned mononuclear nickel(I)-diyne and mononuclear nickel(III)-peroxo species. Spectroscopic experiments on the catalytic reaction mixture also confirm the presence of aforesaid intermediates. Results of both stoichiometric and catalytic reactions suggested an intriguing mechanism involving nickel(II)/nickel(I)/nickel(III) oxidation states in contrast to the reported nickel(II)/nickel(0) catalytic cycle. These findings are expected to open a new paradigm towards nickel-catalyzed organic transformations.

Following the ideas presented in Dahlhaus (2000) and Dahlhaus and Sahm (2000) for time series, we build a Whittle-type approximation of the Gaussian likelihood for locally stationary random fields. To achieve this goal, we extend a Szegö-type formula, for the multidimensional and local stationary case and secondly we derived a set of matrix approximations using elements of the spectral theory of stochastic processes. The minimization of the Whittle likelihood leads to the so-called Whittle estimator \(\widehat{\theta}_{T}\). For the sake of simplicity we assume known mean (without loss of generality zero mean), and hence \(\widehat{\theta}_{T}\) estimates the parameter vector of the covariance matrix \(\Sigma_{\theta}\). We investigate the asymptotic properties of the Whittle estimate, in particular uniform convergence of the likelihoods, and consistency and Gaussianity of the estimator. A main point is a detailed analysis of the asymptotic bias which is considerably more difficult for random fields than for time series. Furthemore, we prove in case of model misspecification that the minimum of our Whittle likelihood still converges, where the limit is the minimum of the Kullback-Leibler information divergence. Finally, we evaluate the performance of the Whittle estimator through computational simulations and estimation of conditional autoregressive models, and a real data application.

Grape powdery mildew, Erysiphe necator, is one of the most significant plant pathogens, which affects grape growing regions world-wide. Because of its short generation time and the production of large amounts of conidia throughout the season, E. necator is classified as a moderate to high risk pathogen with respect to the development of fungicide resistance. The number of fungicidal mode of actions available to control powdery mildew is limited and for some of them resistances are already known. Aryl-phenyl-ketones (APKs), represented by metrafenone and pyriofenone, and succinate-dehydrogenase inhibitors (SDHIs), composed of numerous active ingredients, are two important fungicide classes used for the control of E. necator. Over the period 2014 to 2016, the emergence and development of metrafenone and SDHI resistant E. necator isolates in Europe was followed and evaluated. The distribution of resistant isolates was thereby strongly dependent on the European region. Whereas the north-western part is still predominantly sensitive, samples from east European countries showed higher resistance frequencies. Classical sensitivity tests with obligate biotrophs can be challenging regarding sampling, transport and especially the maintenance of the living strains. Whenever possible, molecular genetic methods are preferred for a more efficient monitoring. Such methods require the knowledge of the resistance mechanisms. The exact molecular target and the resistance mechanism of metrafenone is still unknown. Whole genome sequencing of metrafenone sensitive and resistant wheat powdery mildew isolates, as well as adapted laboratory mutants of Aspergillus nidulans, where performed with the aim to identify proteins potentially linked to the mode of action or which contribute to metrafenone resistance. Based on comparative SNP analysis, four proteins potentially associated with metrafenone resistance were identified, but validation studies could not confirm their role in metrafenone resistance. In contrast to APKs, the mode of action of SDHIs is well understood. Sequencing of the sdh-genes of less sensitive E. necator isolates identified four different target-site mutations, the B-H242R, B-I244V, C-G169D and C-G169S, in sdhB and sdhC, respectively. Based on this information it was possible to develop molecular genetic monitoring methods for the mutations B-H242R and C-G169D. In 2016, the B-H242R was thereby identified as by far the most frequent mutation. Depending on the analysed SDH compound and the sdh-genotype, different sensitivities were observed and revealed a complex cross-resistance pattern. Growth competition assays without selection pressure, with mixtures of sensitive and resistant E. necator isolates, were performed to determine potential fitness costs associated with fungicide resistance. With the experimental setups used, a clear fitness disadvantage associated with metrafenone resistance was not identified, although a strong variability of fitness was observed among the tested resistant E. necator isolates. For isolates with a reduced sensitivity towards SDHIs, associated fitness costs were dependent on the sdh-genotype analysed. Competition tests with the B-H242R genotypes gave evidence that there are no fitness costs associated with this mutation. In contrast, the C-G169D genotypes were less competitive, indicating a restricted fitness compared to the tested sensitive partners. Competition assays of field isolates, which exhibited several resistances towards different fungicide classes, indicated that there are no fitness costs associated with a multiple resistant phenotype in E. necator. Overall, these results clearly indicate the importance to analyse a representative number of isolates with sensitive and resistant phenotypes.

Computational simulations run on large supercomputers balance their outputs with the need of the scientist and the capability of the machine. Persistent storage is typically expensive and slow, its peformance grows at a slower rate than the processing power of the machine. This forces scientists to be practical about the size and frequency of the simulation outputs that can be later analyzed to understand the simulation states. Flexibility in the trade-offs of flexibilty and accessibility of the outputs of the simulations are critical the success of scientists using the supercomputers to understand their science. In situ transformations of the simulation state to be persistently stored is the focus of this dissertation. The extreme size and parallelism of simulations can cause challenges for visualization and data analysis. This is coupled with the need to accept pre partitioned data into the analysis algorithms, which is not always well oriented toward existing software infrastructures. The work in this dissertation is focused on improving current work flows and software to accept data as it is, and efficiently produce smaller, more information rich data, for persistent storage that is easily consumed by end-user scientists. I attack this problem from both a theoretical and practical basis, by managing completely raw data to quantities of information dense visualizations and study methods for managing both the creation and persistence of data products from large scale simulations.

The present situation of control engineering in the context of automated production can be described as a tension field between its desired outcome and its actual consideration. On the one hand, the share of control engineering compared to the other engineering domains has significantly increased within the last decades due to rising automation degrees of production processes and equipment. On the other hand, the control engineering domain is still underrepresented within the production engineering process. Another limiting factor constitutes a lack of methods and tools to decrease the amount of software engineering efforts and to permit the development of innovative automation applications that ideally support the business requirements. This thesis addresses this challenging situation by means of the development of a new control engineering methodology. The foundation is built by concepts from computer science to promote structuring and abstraction mechanisms for the software development. In this context, the key sources for this thesis are the paradigm of Service-oriented Architecture and concepts from Model-driven Engineering. To mold these concepts into an integrated engineering procedure, ideas from Systems Engineering are applied. The overall objective is to develop an engineering methodology to improve the efficiency of control engineering by a higher adaptability of control software and decreased programming efforts by reuse.