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The automatic analysis and retrieval of technical line drawings is hindered by many challenges such as: the large amount of contextual clutter around the symbols within the drawings, degradation, transformations on the symbols in drawings, large databases of drawings
and large alphabets of symbols. The core tasks required for the analysis of technical line
drawings are: symbol recognition, spotting and retrieval. The current systems for performing these tasks have poor performance due to the mentioned challenges. This dissertation
presents a number of methods that address these challenges. These methods achieve both
accurate and efficient symbol spotting and retrieval in technical line drawings, and perform
significantly better than state-of-the-art methods on the same problems. An overview of
the key contributions of this dissertation is given in the following.
First, this dissertation presents a geometric matching-based method for symbol recognition
and spotting. The method performs recognition in the presence of large amounts of contextual clutter, and provides precise localization of the recognized symbols. On standard
databases such as GREC-2005 and GREC-2011, the method achieves up to 10% higher
recall and up to 28% higher precision than state-of-the-art methods on the spotting task,
and achieves up to 7% higher recognition accuracy on the isolated recognition task. The
method is based on a geometric matching approach, which is flexible enough to incorporate
improvements on the matching strategy, feature types and information on the features. The
method also includes an adaptive preprocessing algorithm that deals with a wide variety
of noise types.
In order to improve the performance of the spotting method when dealing with degraded
drawings, two novel methods are presented in this dissertation. Both methods are based on
combining geometric matching with machine learning techniques. The geometric matching
is used to automatically generate training data that contain information on how well the
features of the queries are matched in both the true and the false matches found by the
spotting method. The first method learns the feature weights of the different query symbols
by linear discriminant analysis (LDA). The weighted query features are used in the spotting
method and result in 27% higher average precision than the original method, with a speedup
factor of 2. The second method uses SVM classification as a post-spotting step to distinguish
the true from the false matches in the spotting method. The use of the classification step
further improves the average precision of the spotting method by 20.6%.
This dissertation also presents methods for content analysis of line drawings. First, a
method for accurate and consistent detection (95.8%) of regions of interest (ROIs) is presented. The method is based on statistical feature grouping. The ROI-finding method is
identified as an important part of a symbol retrieval system: the better the detected ROIs,the higher the performance of a retrieval system. The ROI-finding method is also used to
improve the performance of the geometric-based spotting system.
Second, a symbol clustering method for building a compact and accurate representation of
a large database of technical drawings is presented. This method uses the output from the
ROI-finding method as input, and uses geometric matching as a similarity measure. The
method achieves high accuracy (90.1% recall, 94.3% precision) in forming clusters of symbols. The representatives of the clusters (34 symbols) are used as key entries to a symbol
index, which is identified as the outcome of an off-line stage of a symbol retrieval system.
Finally, an efficient and high performing large scale symbol retrieval system is presented
in this dissertation. The system follows the bag of visual words (BoVW) model, but with
using methods that are suitable to line drawings. The system uses the symbol index to
represent a database of drawings. During the on-line query retrieval stage, the query is
analyzed by the ROI-finding method, matched with the key entries of the symbol index via
geometric matching, and finally, a spatial verification step is performed on the retrieved
matches. The system achieves a query lookup time that is independent of the size of the
database, and is instead dependent on the size of the symbol index. The system achieves up
to 10% higher recall and up to 28% higher precision than state-of-the-art spotting systems
on similar databases.
Overall, these contributions are major advancements in the research of graphics recognition.
The hope is that, such contributions provide the basis for the development of reliable and
accurate performing applications for browsing, querying or classification of line drawings
for the benefit of end users.
Many real life problems have multiple spatial scales. In addition to the multiscale nature one has to take uncertainty into account. In this work we consider multiscale problems with stochastic coefficients.
We combine multiscale methods, e.g., mixed multiscale finite elements or homogenization, which are used for deterministic problems with stochastic methods, such as multi-level Monte Carlo or polynomial chaos methods.
The work is divided into three parts.
In the first two parts we study homogenization with different stochastic methods. Therefore we consider elliptic stationary diffusion equations with stochastic coefficients.
The last part is devoted to the study of mixed multiscale finite elements in combination with multi-level Monte Carlo methods. In the third part we consider multi-phase flow and transport equations.
This thesis is separated into three main parts: Development of Gaussian and White Noise Analysis, Hamiltonian Path Integrals as White Noise Distributions, Numerical methods for polymers driven by fractional Brownian motion.
Throughout this thesis the Donsker's delta function plays a key role. We investigate this generalized function also in Chapter 2. Moreover we show by giving a counterexample, that the general definition for complex kernels is not true.
In Chapter 3 we take a closer look to generalized Gauss kernels and generalize these concepts to the case of vector-valued White Noise. These results are the basis for Hamiltonian path integrals of quadratic type. The core result of this chapter gives conditions under which pointwise products of generalized Gauss kernels and certain Hida distributions have a mathematical rigorous meaning as distributions in the Hida space.
In Chapter 4 we discuss operators which are related to applications for Feynman Integrals as differential operators, scaling, translation and projection. We show the relation of these operators to differential operators, which leads to the well-known notion of so called convolution operators. We generalize the central homomorphy theorem to regular generalized functions.
We generalize the concept of complex scaling to scaling with bounded operators and discuss the relation to generalized Radon-Nikodym derivatives. With the help of this we consider products of generalized functions in chapter 5. We show that the projection operator from the Wick formula for products with Donsker's deltais not closable on the square-integrable functions..
In Chapter 5 we discuss products of generalized functions. Moreover the Wick formula is revisited. We investigate under which conditions and on which spaces the Wick formula can be generalized to. At the end of the chapter we consider the products of Donsker's delta function with a generalized function with help of a measure transformation. Here also problems as measurability are concerned.
In Chapter 6 we characterize Hamiltonian path integrands for the free particle, the harmonic oscillator and the charged particle in a constant magnetic field as Hida distributions. This is done in terms of the T-transform and with the help of the results from chapter 3. For the free particle and the harmonic oscillator we also investigate the momentum space propagators. At the same time, the $T$-transform of the constructed Feynman integrands provides us with their generating functional. In Chapter 7, we can show that the generalized expectation (generating functional at zero) gives the Greens function to the corresponding Schrödinger equation.
Moreover, with help of the generating functional we can show that the canonical commutation relations for the free particle and the harmonic oscillator in phase space are fulfilled. This confirms on a mathematical rigorous level the heuristics developed by Feynman and Hibbs.
In Chapter 8 we give an outlook, how the scaling approach which is successfully applied in the Feynman integral setting can be transferred to the phase space setting. We give a mathematical rigorous meaning to an analogue construction to the scaled Feynman-Kac kernel. It is open if the expression solves the Schrödinger equation. At least for quadratic potentials we can get the right physics.
In the last chapter, we focus on the numerical analysis of polymer chains driven by fractional Brownian motion. Instead of complicated lattice algorithms, our discretization is based on the correlation matrix. Using fBm one can achieve a long-range dependence of the interaction of the monomers inside a polymer chain. Here a Metropolis algorithm is used to create the paths of a polymer driven by fBm taking the excluded volume effect in account.
Efficient time integration and nonlinear model reduction for incompressible hyperelastic materials
(2013)
This thesis deals with the time integration and nonlinear model reduction of nearly incompressible materials that have been discretized in space by mixed finite elements. We analyze the structure of the equations of motion and show that a differential-algebraic system of index 1 with a singular perturbation term needs to be solved. In the limit case the index may jump to index 3 and thus renders the time integration into a difficult problem. For the time integration we apply Rosenbrock methods and study their convergence behavior for a test problem, which highlights the importance of the well-known Scholz conditions for this problem class. Numerical tests demonstrate that such linear-implicit methods are an attractive alternative to established time integration methods in structural dynamics. In the second part we combine the simulation of nonlinear materials with a model reduction step. We use the method of proper orthogonal decomposition and apply it to the discretized system of second order. For a nonlinear model reduction to be efficient we approximate the nonlinearity by following the lookup approach. In a practical example we show that large CPU time savings can achieved. This work is in order to prepare the ground for including such finite element structures as components in complex vehicle dynamics applications.
Fluid extraction is a typical chemical process where two types of fluids are mixed together. The high complexity of this process which involves droplet coalescence, breakup, mass transfer, and counter-current flow often makes design difficult. The industrial design of these processes is still based on expensive mini-plant and pilot plant experiments. Therefore, there is a strong need for research into the stimulation of fluid-fluid interaction processes using computational fluid dynamics (CFD).
Previous multi-phase fluid simulations have focused on the development of models that couple mass and momentum using the Navier-Stokes equation. Recent population balance models (PBM) have proved to be important methods for analyzing droplet breakage and collisions. A combination of CFD and PBM facilitates the simulation of flow property by solving coupling equations, and the calculation of the droplet size and numbers. In our study, we successfully coupled an Euler-Euler CFD model with the breakup and coalescence models proposed by Luo and Svendsen (59).
The simulation output of extraction columns provides a mathematical understand- ing of how fluids are mixed inside a mixing device. This mixing process shows that the dispersed phase of a flow generates large blobs and bubbles. Current mathemati- cal simulation results often fail to provide an intuitive representation of how well two different types of fluid interact, so intuitive and physically plausible visualization tech- niques are in high demand to help chemical engineers to explore and analyze bubble column simulation data. In chapter 3, we present the visualization tools we developed for extraction column data.
Fluid interfaces and free surfaces are topics of growing interest in the field of multi- phase computational fluid dynamics. However, the analysis of the flow field relative to the material interface shape and topology is a challenging task. In chapter 5, we present a technique that facilitates the visualization and analysis of complex material interface behaviors over time. To achieve this, we track the surface parameterization of time-varying material interfaces and identify locations where there are interactions between the material interfaces and fluid particles. Splatting and surface visualization techniques produce an intuitive representation of the derived interface stability. Our results demonstrate that the interaction of a flow field with a material interface can be understood using appropriate extraction and visualization techniques, and that our techniques can help the analysis of mixing and material interface consistency.
In addition to texture-based methods for surface analysis, the interface of two- phase fluid can be considered as an implicit function of the density or volume fraction values. High-level visualization techniques such as topology-based methods can re- veal the hidden structure underlying simple simulation data, which will enhance and advance our understanding of multi-fluid simulation data. Recent feature-based vi- sualization approaches have explored the possibility of using Reeb graphs to analyze scalar field topologies(19, 107). In chapter 6, we present a novel interpolation scheme for interpolating point-based volume fraction data and we further explore the implicit fluid interface using a topology-based method.
Cyanobacteria are the only prokaryotes with the ability to conduct oxygenic photosynthesis,
therefore having major influence on the evolution of life on earth. Their diverse morphology
was traditionally the basis for taxonomy and classification. For example, the genus
Chroococcidiopsis has been classified within the order Pleurocapsales, based on a unique
reproduction modus by baeocytes. Recent phylogenetic results suggested a closer
relationship of this genus to the order Nostocales. However, these studies were based
mostly on the highly conserved 16S rRNA and a small selection of Chroococcidiopsis
strains. One aim of this present thesis was to investigate the evolutionary relationships of
the genus Chroococcidiopsis, the Pleurocapsales and remaining cyanobacteria using
16S rRNA, rpoC1 and gyrB gene. Including the single gene, as the multigene analyses of
97 strains clearly showed a separation of the genus Chroococcidiopsis from the
Pleurocapsales. Furthermore, a sister relationship between the genus Chroococcidiopsis
and the order Nostocales was confirmed. Consequently, the monogeneric family
Chroococcidiopsidaceae Geitler ex. Büdel, Donner & Kauff familia nova is justified. The
phylogenetic analyses also revealed the polyphyly of the remaining Pleurocapsales, due to
the fact that the strain Pleurocapsa PCC 7327 was always separated from other strains.
This is supported by differences in their metabolism, ecology and physiology.
A second aim of this study was to investigate the thylakoid arrangement of
Chroococcidiopsis and a selection of cyanobacterial strains. The investigation of 13 strains
with Low Temperature Scanning Electron Microscopy revealed two unknown thylakoidal
arrangements within Chroococcidiopsis (parietal and stacked). This result revised the
knowledge of the thylakoid arrangement in this genus. Previously, only a coiled
arrangement was known for three strains. Based on the data of 66 strains, the feature
thylakoid arrangement was tested as a potential feature for morphological identification of
cyanobacteria. The results showed a strong relationship between the group assignment of
cyanobacteria and their thylakoid arrangements. Hence, it is in general possible to
conclude from this certain phenotypic character the affiliation to a particular family, order
or genus.
The third aim of this study was to investigate biogeographical patterns of the worldwide
distributed genus Chroococcidiopsis. The phylogenetic analysis suggested that the genus do not have biogeographical patterns, which is in contrast with a recent study on hypolithic
living Chroococcidiopsis strains and the majority of phylogeographic analysis of
microorganisms. Further analysis showed no separation of different life-strategies within
the genus. These results could be related to the genetic markers utilized, which may not
contain biogeographical information. Hence the present study can neither exclude nor
prove the possibility of biogeographic and life-strategy patterns in the genus
Chroococcidiopsis.
Future research should be focused on finding appropriate genetic markers investigate of
evolutionary relationships and biogeographical patterns within Chroococcidiopsis.
The use of trading stops is a common practice in financial markets for a variety of reasons: it provides a simple way to control losses on a given trade, while also ensuring that profit-taking is not deferred indefinitely; and it allows opportunities to consider reallocating resources to other investments. In this thesis, it is explained why the use of stops may be desirable in certain cases.
This is done by proposing a simple objective to be optimized. Some simple and commonly-used rules for the placing and use of stops are investigated; consisting of fixed or moving barriers, with fixed transaction costs. It is shown how to identify optimal levels at which to set stops, and the performances of different rules and strategies are compared. Thereby, uncertainty and altering of the drift parameter of the investment are incorporated.
Recent progresses and advances in the field of consumer electronics, driven by display
technologies and also the sector of mobile, hand-held devices, enable new ways in
presenting information to users, as well as new ways of user interaction, therefore
providing a basis for user-centered applications and work environments.
My thesis focuses on how arbitrary display environments can be utilized to improve
both the user experience, regarding perception of information, and also to provide
intuitive interaction possibilities. On the one hand advances in display technologies
provide the basis for new ways of visualizing content and collaborative work, on the
other hand forward-pressing developments in the consumer market, especially the
market of smart phones, offer potential to enhance usability in terms of interaction
and therefore can provide additional benefit for users.
Tiled display setups, combining both large screen real estate and high resolution,
provide new possibilities and chances to visualize large datasets and to facilitate col-
laboration in front of a large screen area. Furthermore these display setups present
several advantages over the traditional single-user-workspace environments: con-
trary to single-user-workspaces, multiple users are able to explore a dataset displayed
on a tiled display system, at the same time, thus allowing new forms of collabora-
tive work. Based on that, face-to-face discussions are enabled, an additional value
is added. Large displays also allow the utilization of the user’s spatial memory, al-
lowing physical navigation without the need of switching between different windows
to explore information.
With Tiled++ I contributed a versatile approach to address the bezel problem. The
bezel problem is one of the Top Ten research challenges in the research field of LCD-
based tiled wall setups. By applying the Tiled++ approach a large high resolution
Focus & Context screen is created, combining high resolution focus areas with low
resolution context information, projected onto the bezel area.
Additionally the field of user interaction poses an important challenge, especially
regarding the utilization of large tiled displays, since traditional keyboard & mouse
interaction devices reached their limits. My focus in this thesis is on Mobile HCI.Devices like mobile phones are utilized to interact with large displays, since they
feature various interaction modalities and preserve user mobility.
Large public displays, as a modernized form of traditional bulletin boards, also en-
able new ways of handling information, displaying content, and user interaction.
Utilized in hot spots, Digital Interactive Public Pinboards can provide an adequate
answer to questions like how to approach pressing issues like disaster and crisis man-
agement for both responders as well as citizens and also new ways of how to handle
information flow (contribution & distribution & accession). My contribution to the
research field of public display environments was the conception and implementa-
tion of an easy-to-use and easy-to-set-up architecture to overcome shortcomings of
current approaches and to cover the needs of aid personnel.
Although being a niche, Virtual Reality (VR) environments can provide additional
value for visualizing specific content. Disciplines like earth sciences & geology, me-
chanical engineering, design, and architecture can benefit from VR environments. In
order to consider the variety of users, I introduce a more intuitive and user friendly
interaction metaphor, the ARC metaphor.
Visualization challenges base on being able to cope with more and more complex
datasets and to bridge the gap between comprehensibility and loss of information.
Furthermore the visualization approach has to be reasonable, which is a crucial
factor when working in interdisciplinary teams, where the standard of knowledge
is diverse. Users have to be able to conceive the visualized content in a fast and
reliable way. My contribution are visualization approaches in the field of supportive
visualization.
Finally, my work illuminates how the synthesis of visualization, interaction and dis-
play technologies enhance the user experience. I promote a holistic view. The user
is brought back into the focus of attention, provided with a tool-set to support him,
without overextending the abilities of, for example, non-expert users, a crucial factor
in the more and more interdisciplinary field of computer science.
This thesis provides a fully automatic translation from synchronous programs to parallel software for different architectures, in particular, shared memory processing (SMP) and distributed memory systems. Thereby, we exploit characteristics of the synchronous model of computation (MoC) to reduce communication and to improve available parallelism and load-balancing by out-of-order (OOO) execution and data speculation.
Manual programming of parallel software requires the developers to partition a system into tasks and to add synchronization and communication. The model-based approach of development abstracts from details of the target architecture and allows to make decisions about the target architecture as late as possible. The synchronous MoC supports this approach by abstracting from time and providing implicit parallelism and synchronization. Existing compilation techniques translate synchronous programs into synchronous guarded actions (SGAs) which are an intermediate format abstracting from semantic problems in synchronous languages. Compilers for SGAs analyze causality problems, ensure logical correctness and the absence of schizophrenia problems. Hence, SGAs are a simplified and general starting point and keep the synchronous MoC at the same time. The instantaneous feedback in the synchronous MoC makes the mapping of these systems to parallel software a non-trivial task. In contrast, other MoCs such as data-flow processing networks (DPNs) directly match with parallel architectures. We translate the SGAs into DPNs,which represent a commonly used model to create parallel software. DPNs have been proposed as a programming model for distributed parallel systems that have communication paths with unpredictable latencies. The purely data-driven execution of DPNs does not require a global coordination and therefore DPNs can be easily mapped to parallel software for architectures with distributed memory. The generation of efficient parallel code from DPNs challenges compiler design with two issues: To perfectly utilize a parallel system, the communication and synchronization has to be kept low, and the utilization of the computational units has to be balanced. The variety of hardware architectures and dynamic execution techniques in processing units of these systems make a statically balanced distributed execution impossible.
The synchronous MoC is still reflected in our generated DPNs, which exhibits characteristics that allow optimizations concerning the previously mentioned issues. In particular, we apply a general communication reduction and OOO execution to achieve a dynamically balanced execution which is inspired from hardware design.
Polychlorinated dibenzo-p-dioxins, dibenzofurans, and polychlorinated biphenyls are persistent environmental pollutants which ubiquitously occur as complex mixtures and accumulate in the food and feed chain due to their high lipophilic properties. Of the 419 possible congeners, only 29 share a common mechanism of action and cause similar effects, the so called dioxin-like compounds. Dioxin-like compounds evoke a broad spectrum of biochemical and toxic responses, i.e. enzyme induction, dermal toxicity, hepatotoxicity, immunotoxicity, carcinogenicity as well as adverse effects on reproduction, development, and the endocrine system in laboratory animals and in humans. Most, if not all, of the aforementioned responses, are mediated by the aryl hydrocarbon receptor. In the present work, the elicited biochemical effects of a selection of dioxin-like compounds and the non dioxin-like PCB 153 were examined in mouse (in vivo) and in human liver cell models (in vitro). Emphasis was given to the main contributors to the total toxic equivalents in human blood and tissues TCDD, 1-PnCDD, 4-PnCDF, PCB 118, PCB 126, and PCB 156, which likewise contribute about 90 % to the dioxin-like activity in the human food chain.
Three mouse in vivo studies were carried out aiming to characterize the alterations in hepatic gene expression as well as the induction of hepatic xenobiotic metabolizing enzymes after single oral dose. Based on the results obtained from mouse 3-day and 14-day studies, the seven test compounds can be categorized into three classes; the ones which are 'pure' AhR ligands (TCDD, 1-PnCDD, 4-PnCDF, and PCB 126) or solely CAR inducers (PCB 153), and the ones which are AhR/CAR mixed-type inducers (PCB 118, PCB 156). Moreover, the analysis of hepatic gene expression patterns after a single oral dose of either TCDD or PCB 153 revealed that the altered genes fundamentally differed. Profiling of significantly altered genes led to the conclusion that changes in gene expression were associated with different signalling pathways, in fact by AhR and CAR.
For investigating the role of the AhR in mediating biological responses, several experimental approaches were carried out, such as the analysis of blood plasma metabolites in Ahr knockout and wild-type mice. Genotype specifics and similarities were determined by HPLC-MS/MS analysis. Several plasma metabolites could be identified in both genotypes, but also differences were detected. Furthermore, an in vivo experiment was performed aiming to characterize AhR-dependent and -independent effects in female Ahr knockout and wild-type mice. For this purpose, mice received a single oral dose of TCDD and were killed 96 h later. Microarray analysis of mouse livers revealed that although the Ahr gene was knocked out in Ahr-/- mice, the quantity of affected genes were in the same order of magnitude as for Ahr+/+ mice, but the pattern of altered genes distinctly differed. In addition, the relative liver weights of TCDD-treated Ahr+/+ mice were significantly increased which led to the conclusion, that TCDD induced the development of hepatic steatosis in female Ahr wild-type.
The performed in vitro experiments aimed to characterize the effects elicited by selected DLCs and PCB 153 in human liver cell models by the use of HepG2 cells and primary human hepatocytes. In general, primary human hepatocytes were less responsive than HepG2 cells. This was not only observed in EC values derived from EROD assay, but also regarding microarray analysis in terms of differently regulated genes. In vitro REPs gained from both liver cell models widely confirmed the current TEFs, but some deviations occurred. The comparison of the TCDD-altered genes in both human cell types revealed that only a considerably small number of genes was in common up regulated by both human liver cell models, such as the established AhR-regulated highly inducible cytochrome P450s 1A1, 1A2, and 1B1 as well as other AhR target genes. Although the overlap was rather small, the TCDD-induced genes could be consistently associated with the broad spectrum of established dioxin-related biological responses. The gene expression pattern in primary human hepatocytes after treatment with selected DLCs (TCDD, 1-PnCDD, 4-PnCDF, and PCB 126) and PCB 153 was additionally characterized by microarray analysis. The highest response in terms of significantly altered genes was determined for TCDD, followed by 4-PnCDF, 1-PnCDD, and PCB 126, whereas exposure to PCB 153 did not evoke any significant changes in gene expression. The pattern of significantly altered genes was very homogenous among the four congeners. Genes associated with well-established DLC-related biological responses as well as novel dioxin-inducible target genes were identified, whereby an extensive overlap in terms of up regulated genes by all four DLCs occurred. In conclusion, the results from the in vitro experiments performed in primary human hepatocytes provided fundamental insight into the congeners' potencies and caused alterations in gene expression patterns. The obtained findings implicate that although the extent of enzyme inducibilities varied, the gene expression patterns are coincidental. Microarray analysis identified species-specific (mouse vs. human) as well as model-specific (in vitro vs. in vivo and transformed cells vs. untransformed cells) differences. In order to identify novel biomarkers for AhR activation due to treatment with dioxin-like compounds, five candidates were selected based on the microarray results i.e. ALDH3A1, TIPARP, HSD17B2, CD36, and AhRR. Eventually, ALDH3A1 turned out to be the most reliable and suitable marker for exposure to DLCs in both human liver cell models eliciting the highest mRNA inducibility among the five chosen candidates. In which way these species- and cell type-specific markers are involved in the dioxin-elicited toxic responses should be further characterized in vivo and in vitro.
The noise issue in manufacturing system is widely discussed from legal and health aspects. Regarding the existing laws and guidelines, various investigation methods are implemented in industry. The sound pressure level can be measured and reduced by using established approaches in reality. However, a straightforward and low cost approach to study noise issue using existing digital factory models is not found.
This thesis attempts to develop a novel concept for sound pressure level investigation in a virtual environment. With this, the factory planners are able to investigate the noise issue during factory design and layout planning phase.
Two computer aided tools are used in this approach: acoustic simulation and virtual reality (VR). The former enables the planner to simulate the sound pressure level by given factory layout and facility sound features. And the latter provides a visualization environment to view and explore the simulation results. The combination of these two powerful tools provides the planners a new possibility to analyze the noise in a factory.
To validate the simulations, the acoustic measurements are implemented in a real factory. Sound pressure level and sound intensity are determined respectively. Furthermore, a software tool is implemented using the introduced concept and approach. With this software, the simulation results are represented in a Cave Automatic Virtual Environment (CAVE).
This thesis describes the development of the approach, the measurement of sound features, the design of visualization framework, and the implementation of VR software. Based on this know-how, the industry users are able to design their own method and software for noise investigation and analysis.
Constructing accurate earth models from seismic data is a challenging task. Traditional methods rely on ray based approximations of the wave equation and reach their limit in geologically complex areas. Full waveform inversion (FWI) on the other side seeks to minimize the misfit between modeled and observed data without such approximation.
While superior in accuracy, FWI uses a gradient based iterative scheme that makes it also very computationally expensive. In this thesis we analyse and test an Alternating Direction Implicit (ADI) scheme in order to reduce the costs of the two dimensional time domain algorithm for solving the acoustic wave equation. The ADI scheme can be seen as an intermediate between explicit and implicit finite difference modeling schemes. Compared to full implicit schemes the ADI scheme only requires the solution of much smaller matrices and is thus less computationally demanding. Using ADI we can handle coarser discretization compared to an explicit method. Although order of convergence and CFL conditions for the examined explicit method and ADI scheme are comparable, we observe that the ADI scheme is less prone to dispersion. Furhter, our algorithm is efficiently parallelized with vectorization and threading techniques. In a numerical comparison, we can demonstrate a runtime advantage of the ADI scheme over an explicit method of the same accuracy.
With the modeling in place, we test and compare several inverse schemes in the second part of the thesis. With the goal of avoiding local minima and improving speed of convergence, we use different minimization functions and hierarchical approaches. In several tests, we demonstrate superior results of the L1 norm compared to the L2 norm – especially in the presence of noise. Furthermore we show positive effects for applying three different multiscale approaches to the inverse problem. These methods focus on low frequency, early recording, or far offset during early iterations of the minimization and then proceed iteratively towards the full problem. We achieve best results with the frequency based multiscale scheme, for which we also provide a heuristical method of choosing iteratively increasing frequency bands.
Finally, we demonstrate the effectiveness of the different methods first on the Marmousi model and then on an extract of the 2004 BP model, where we are able to recover both high contrast top salt structures and lower contrast inclusions accurately.
There is a growing trend for ever larger wireless sensor networks (WSNs) consisting of thousands or tens of thousands of sensor nodes (e.g., [91, 79]). We believe this trend will continue and thus scalability plays a crucial role in all protocols and mechanisms for WSNs. Another trend in many modern WSN applications is the time sensitivity to information from sensors to sinks. In particular, WSNs are a central part of the vision of cyber-physical systems and as these are basically closed-loop systems many WSN applications will have to operate under stringent timing requirements. Hence, it is crucial to develop algorithms that minimize the worst-case delay in WSNs. In addition, almost all WSNs consist of battery-powered nodes, and thus energy-efficiency clearly remains another premier goal in order to keep network lifetime high. This dissertation presents and evaluates designs for WSNs using multiple sinks to achieve high lifetime and low delay. Firstly, we investigate random and deterministic node placement strategies for large-scale and time-sensitive WSNs. In particular, we focus on tiling-based deterministic node placement strategies and analyze their effects on coverage, lifetime, and delay performance under both exact placement and stochastically disturbed placement. Next, we present sink placement strategies, which constitutes the main contributions of this dissertation. Static sinks will be placed and mobile sinks will be given a trajectory. A proper sink placement strategy can improve the performance of a WSN significantly. In general, the optimal sink placement with lifetime maximization is an NP-hard problem. The problem is even harder if delay is taken into account. In order to achieve both lifetime and delay goals, we focus on the problem of placing multiple (static) sinks such that the maximum worst-case delay is minimized while keeping the energy consumption as low as possible. Different target networks may need a corresponding sink placement strategy under differing levels of apriori assumptions. Therefore, we first develop an algorithm based on the Genetic Algorithm (GA) paradigm for known sensor nodes' locations. For a network where global information is not feasible we introduce a self-organized sink placement (SOSP) strategy. While GA-based sink placement achieves a near-optimal solution, SOSP provides a good sink placement strategy with a lower communication overhead. How to plan the trajectories of many mobile sinks in very large WSNs in order to simultaneously achieve lifetime and delay goals had not been treated so far in the literature. Therefore, we delve into this difficult problem and propose a heuristic framework using multiple orbits for the sinks' trajectories. The framework is designed based on geometric arguments to achieve both, high lifetime and low delay. In simulations, we compare two different instances of our framework, one conceived based on a load-balancing argument and one based on a distance minimization argument, with a set of different competitors spanning from statically placed sinks to battery-state aware strategies. We find our heuristics outperform the competitors in both, lifetime and delay. Furthermore, and probably even more important, the heuristic, while keeping its good delay and lifetime performance, scales well with an increasing number of sinks. In brief, the goal of this dissertation is to show that placing nodes and sinks in conventional WSNs as well as planning trajectories in mobility enabled WSNs carefully really pays off for large-scale and time-sensitive WSNs.
Due to tremendous improvements of high-performance computing resources as well
as numerical advances computational simulations became a common tool for modern
engineers. Nowadays, simulation of complex physics is more and more substituting a
large amount of physical experiments. While the vast compute power of large-scale
high-performance systems enabled for simulating more complex numerical equations,
handling the ever increasing amount of data with spatial and temporal resolution
burdens new challenges to scientists. Huge hardware and energy costs desire for
ecient utilization of high-performance systems. However, increasing complexity of
simulations raises the risk of failing simulations resulting in a single simulation to be
restarted multiple times. Computational Steering is a promising approach to interact
with running simulations which could prevent simulation crashes. The large amount
of data expands gaps in the amount of data that can be calculated and the amount of
data that can be processed. Extreme-scale simulations produce more data that can
even be stored. In this thesis, I propose several methods that enhance the process
of steering, exploring, visualizing, and analyzing ongoing numerical simulations.
The research presented in this PhD thesis is a contribution to the field of anion recognition in competitive aqueous solvent mixtures. Neutral anion receptors having a cage-type architecture have been developed on the basis of triply-linked bis(cyclopeptides) and their binding properties toward various inorganic anions have been studied.
The synthetic approaches chosen to assemble the targeted container molecules rely on dynamic chemistry under the template effects of anions such as sulfate and halides. As reversible reactions metal-ligand exchange and thiol-disulfide exchange were used. Disulfide exchange has previously provided singly- and doubly-linked bis(cyclopeptide) receptors whose anion affinities in 2:1 acetonitrile/water mixtures approached the nanomolar range. Metal-ligand interactions have so far not been used to assemble bis(cyclopeptides) in our group. The cyclopeptide building blocks required for both approaches, namely cyclic hexapeptides containing alternating 6-aminopicolinic acid and either (2S,4S)-4-cyanoproline or (2S,4S)-4-thioproline subunits could be synthesized successfully.
Self-assembly of the bis(cyclopeptide) held together by coordinative interactions has been attempted by treating the cyclopeptide trinitrile with square-planar palladium (II) complexes. The reaction was followed with different NMR spectroscopic techniques. Unfortunately, none of the experiments provides conclusive evidence that the targeted triply-linked cage was indeed formed.
Bis(cyclopeptides) containing three dithiol derived linkers between the cyclopeptide rings could be synthesizes successfully. Two complexes were isolated, albeit in small amounts, one containing linkers derived from 1,2-ethanedithiol and the other one from 1,3-benzenedithiol that contain a sulfate anion incorporated in the cavity between the cyclopeptide rings. Formation of triply-linked bis(cyclopeptides) containing different types of linkers could be achieved by performing the synthesis in the presence of different dithiols. Unfortunately, the two C3 symmetrical bis(cyclopeptides) containing a single linker type could not be isolated in analytically pure form so that only qualitative binding studies could be performed. Investigations in this context indicate extraordinary sulfate affinity for these bis(cyclopeptides). In particular, affinity of the receptor containing the 1,2-ethanedithiol linkers for sulfate anions is so high that is even able to dissolve barium sulfate under appropriate conditions and presumably exceeds the sulfate affinity of the doubly-linked bis(cyclopeptides). The sulfate anion present in the cavity of this bis(cyclopeptide) can be replaced by a large number of other anions, i.e. by selenate, perrhenate, nitrate, tetrafluoroborate, hexafluorophosphate and halides. None of these complexes proved to be as stable as the corresponding sulfate complex. In addition, 1H-NMR spectroscopic investigations provided information about the solution structure of the bis(cyclopeptide) anion complexes. Sulfate release from the cavity of the receptor is a slow process while exchange of other anions is significantly faster. Another interesting feature that has been observed for sulfate and selenate complexes of the 1,2-ethanedithiol-containing bis(cyclopeptide) is the very slow H/D rate with which protons on amide groups located inside the cavity of the cage are replaced by deuterium atoms in protic deuterated solvents. This effect in combination with the observation that the different deuterated bis(cyclopeptide) species exhibit individual amide NH signals in the 1H-NMR spectrum are indicative for well defined complex geometries with strong hydrogen-bonding interactions between the anion and the amide NH groups of the receptor. Following the H/D exchange rate in the presence of various salts indicated that anion exchange proceeds via the dissociated complex and not by direct replacement of one anion by another one.
Aim of this work was the extension and development of a coupled Computational Fluid Dynamics (CFD) and population balance model (PBM) solver to enable a simulation aided design of stirred liquid-liquid extraction columns. The principle idea is to develop a new design methodology based on a CFD-PBM approach and verify it with existing data and correlations. On this basis, the separation performance in any apparatus geometry should be possible to predict without any experimental input. Reliable “experiments in silico” (computer calculations) should give the engineer a valuable and user-friendly tool for early design studies at minimal costs.
The layout of extraction columns is currently based on experimental investigations from miniplant to pilot plant and a scale-up to the industrial scale. The hydrodynamic properties can be varied by geometrical adjustments of the stirrer diameter, the stirrer height, the free cross sectional area of the stator, the compartment height as well as the positioning and the size of additional baffles. The key parameter for the liquid–liquid extraction is the yield which is mainly determined at the in- and outlets of the column. Local phenomena as the swirl structure are influenced by geometry changes. However, these local phenomena are generally neglected in state-of-the are design methodologies due to the complex required measurement techniques. A geometrical optimization of the column therefore still results in costs for validation experiments as assembly and operation of the column, which can be reduced by numerical investigations. The still mainly in academics used simulation based layout of counter-current extraction columns is based at the beginning of this work on one dimensional simulations of extraction columns and first three dimensional simulations. The one dimensional simulations are based on experimental derived, geometrical dependent correlations for the axial backmixing (axial dispersion), the hold-up, the phase fraction, the droplet sedimentation and the energy dissipation. A combination of these models with droplet population balance modeling resulted in a description of the complex droplet-droplet interactions (droplet size) along the column height. The three dimensional CFD simulations give local information about the flow field (velocity, swirl structure) based on the used numerical mesh corresponding to the real geometry. A coupling of CFD with population balance modeling further provides information about the local droplet size. A backcoupling of the droplet size with the CFD (drag model) results in an enhancement of the local hydrodynamics (e.g. hold-up, dispersed phase velocity). CFD provided local information about the axial dispersion coefficient of simple geometrical design (e.g. Rotating Disc Contactor (RDC) column). First simulations of the RDC column using a two dimensional rotational geometry combined with population balance modeling were performed and gave local information about the droplet size for different boundary conditions (rotational speed, different column sizes).
In this work, two different column types were simulated using an extended OpenSource CFD code. The first was the RDC column, which were mainly used for code development due to its simple geometry. The Kühni DN32 column is equipped with a six-baffled stirring device and flat baffles for disturbing the flow and requires a full three dimensional description. This column type was mainly used for experimental validation of the simulations due to the low required volumetric flow rate. The Kühni DN60 column is similar to the Kühni DN32 column with slight changes to the stirring device (4-baffles) and was used for scale up investigations. For the experimental validation of the hydrodynamics, laser based measurement techniques as Particle Image Velocimetry (PIV) and Laser Induced Fluorescence (LIF) were used. A good agreement between the experimental derived values for velocity, hold-up and energy dissipation, experimentally derived correlations from literature and the simulations with a modified Euler-Euler based OpenSource CFD code could be found. The experimental derived axial dispersion coefficient was further compared to Euler-Lagrange simulations. The experimental derived correlations for the Kühni DN32 in literature fit to the simulated values. Also the axial dispersion coefficient for the dispersed phase satisfied a correlation from literature. However, due to the complexity of the dispersed phase axial dispersion coefficient measurement, the available correlations gave no distinct agreement to each other.
A coupling of the modified Euler-Euler OpenSource CFD code was done with a one group population balance model. The implementation was validated to the analytical solution of the population balance equation for constant breakage and coalescence kernels. A further validation of the population balance transport equation was done by comparing the results of a five compartment section to the results of the commercial CFD code FLUENT using the Quadrature Method of Moments (QMOM).
For the simulation of the droplet-droplet interactions in liquid-liquid extraction columns, several breakage and coalescence models are available in the literature. The models were compared to each other using the one-group population balance model in Matlab which allows the determination of the minimum stable droplet diameter at a certain energy dissipation. Based on this representation, it was possible to determine the parameters for a specific breakage and coalescence model combination which allowed the simulation of a Kühni miniplant column at different rotational speeds. The resulting simulated droplet size was in very good agreement to the experimental derived droplet size from literature. Several column designs of the DN32 were investigated by changing the compartment height and the axial stirrer position. It could be shown that a decrease of the stirrer position increases the phase fraction inside the compartment. At the same time, the droplet size decreases inside the compartment, which allows a higher mass transfer due to a higher available interfacial area. However, the shifting results in an expected earlier flooding of the column due to a compressed flow structure underneath the stirring device. In a next step, the code was further extended by mass transfer equations based on the two-film theory. Mass transfer coefficient models for the dispersed and continuous phase were investigated for the RDC column design.
A first mass transfer simulation of a full miniplant column was done. The change in concentration was accounted by the mixture density, viscosity and interfacial tension in dependence of the concentration, which affects the calculation of the droplet size. The results of the column simulation were compared to own experimental data of the column. It could be shown that the concentration profile along the column height can be predicted by the presented CFD/population balance/mass transfer code. The droplet size decreases corresponding to the interfacial tension along the column height. Compared to the experimental derived droplet size at the outlet, the simulation is in good agreement.
Besides the occurrence of a mono dispersed droplet size, high breakage may lead to the generation of small satellite droplets and coalescence underneath the stator leads to larger droplets inside the column and hence to a change of the hold-up and of the flooding point. A multi-phase code was extended by the Sectional Quadrature Method of Moment (SQMOM) allowing a modeling of the droplet interactions of bimodal droplet interactions or multimodal distributions. The implementations were in good agreement to the analytical solution. In addition, the simulation of an RDC column section showed the different distribution of the smaller droplets and larger droplets. The smaller droplets tend to follow the continuous phase flow structure and show a higher distribution of inside the column. The larger droplets tend to rise directly through the column and show only a low influence to the continuous phase flow.
The current results strengthen the use of CFD for the layout of liquid-liquid extraction columns in future. The coupling of CFD/PBM and mass transfer using an OpenSource CFD code allows the investigation of computational intensive column designs (e.g. pilot plant columns). Furthermore the coupled code enhances the accuracy of the hydrodynamics simulations and leads to a better understanding of counter-current liquid-liquid extraction columns. The gained correlation were finally used as an input for one dimensional mass transfer simulations, where a perfect fit of the concentration profiles at varied boundary conditions could be obtained. By using the multi-scale approach, the computational time for mass transfer simulations could be reduced to minutes. In future, with increasing computational power, a further extend of the multiphase CFD/SQMOM model including mass transfer equation will provide an efficient tool to model multimodal and multivariate systems as bubble column reactors.
Tire-soil interaction is important for the performance of off-road vehicles and the soil compaction in the agricultural field. With an analytical model, which is integrated in multibody-simulation software, and a Finite Element model, the forces and moments generated on the tire-soil contact patch were studied to analyze the tire performance. Simulations with these two models for different tire operating conditions were performed to evaluate the mechanical behaviors of an excavator tire. For the FE model validation a single wheel tester connected to an excavator arm was designed. Field tests were carried out to examine the tire vertical stiffness, the contact pressure on the tire – hard ground interface, the longitudinal/vertical force and the compaction of the sandy clay from the test field under specified operating conditions. The simulation and experimental results were compared to evaluate the model quality. The Magic Formula was used to fit the curves of longitudinal and lateral forces. A simplified tire-soil interaction model based on the fitted Magic Formula could be established and further applied to the simulation of vehicle-soil interaction.
In the last few years a lot of work has been done in the investigation of Brownian motion with point interaction(s) in one and higher dimensions. Roughly speaking a Brownian motion with point interaction is nothing else than a Brownian motion whose generator is disturbed by a measure supported in just one point.
The purpose of the present work is the introducing of curve interactions of the two dimensional Brownian motion for a closed curve \(\mathcal{C}\). We will understand a curve interaction as a self-adjoint extension of the restriction of the Laplacian to the set of infinitely often continuously differentiable functions with compact support in \(\mathbb{R}^{2}\) which are constantly 0 at the closed curve. We will give a full description of all these self-adjoint extensions.
In the second chapter we will prove a generalization of Tanaka's formula to \(\mathbb{R}^{2}\). We define \(g\) to be a so-called harmonic single layer with continuous layer function \(\eta\) in \(\mathbb{R}^{2}\). For such a function \(g\) we prove
\begin{align}
g\left(B_{t}\right)=g\left(B_{0}\right)+\int\limits_{0}^{t}{\nabla g\left(B_{s}\right)\mathrm{d}B_{s}}+\int\limits_{0}^{t}\eta\left(B_{s}\right)\mathrm{d}L\left(s,\mathcal{C}\right)
\end{align}
where \(B_{t}\) is just the usual Brownian motion in \(\mathbb{R}^{2}\) and \(L\left(t,\mathcal{C}\right)\) is the connected unique local time process of \(B_{t}\) on the closed curve \(\mathcal{C}\).
We will use the generalized Tanaka formula in the following chapter to construct classes of processes related to curve interactions. In a first step we get the generalization of point interactions in a second step we get processes which behaves like a Brownian motion in the complement of \(\mathcal{C}\) and has an additional movement along the curve in the time- scale of \(L\left(t,\mathcal{C}\right)\). Such processes do not exist in the one point case since there we cannot move when the Brownian motion is in the point.
By establishing an approximation of a curve interaction by operators of the form Laplacian \(+V_{n}\) with "nice" potentials \(V_{n}\) we are able to deduce the existence of superprocesses related to curve interactions.
The last step is to give an approximation of these superprocesses by a sytem of branching particles. This approximation gives a better understanding of the related mass creation.
This thesis is divided into two parts. Both cope with multi-class image segmentation and utilize
non-smooth optimization algorithms.
The topic of the first part, namely unsupervised segmentation, is the application of clustering
to image pixels. Therefore, we start with an introduction of the biconvex center-based clustering
algorithms c-means and fuzzy c-means, where c denotes the number of classes. We show that
fuzzy c-means can be seen as an approximation of c-means in terms of power means.
Since noise is omnipresent in our image data, these simple clustering models are not suitable
for its segmentation. To this end, we introduce a general and finite dimensional segmentation
model that consists of a data term stemming from the aforementioned clustering models plus a
continuous regularization term. We tackle this optimization model via an alternating minimiza-
tion approach called regularized c-centers (RcC). Thereby, we fix the centers and optimize the
segment membership of the pixels and vice versa. In this general setting, we prove convergence
in the sense of set-valued algorithms using Zangwill’s Theory [172].
Further, we present a segmentation model with a total variation regularizer. While updating
the cluster centers is straightforward for fixed segment memberships of the pixels, updating the
segment membership can be solved iteratively via non-smooth, convex optimization. Thereby,
we do not iterate a convex optimization algorithm until convergence. Instead, we stop as soon as
we have a certain amount of decrease in the objective functional to increase the efficiency. This
algorithm is a particular implementation of RcC providing also the corresponding convergence
theory. Moreover, we show the good performance of our method in various examples such as
simulated 2d images of brain tissue and 3d volumes of two materials, namely a multi-filament
composite superconductor and a carbon fiber reinforced silicon carbide ceramics. Thereby, we
exploit the property of the latter material that two components have no common boundary in
our adapted model.
The second part of the thesis is concerned with supervised segmentation. We leave the area
of center based models and investigate convex approaches related to graph p-Laplacians and
reproducing kernel Hilbert spaces (RKHSs). We study the effect of different weights used to
construct the graph. In practical experiments we show on the one hand image types that
are better segmented by the p-Laplacian model and on the other hand images that are better
segmented by the RKHS-based approach. This is due to the fact that the p-Laplacian approach
provides smoother results, while the RKHS approach provides often more accurate and detailed
segmentations. Finally, we propose a novel combination of both approaches to benefit from the
advantages of both models and study the performance on challenging medical image data.
Backward compatibility of class libraries ensures that an old implementation of a library can safely be replaced by a new implementation without breaking existing clients.
Formal reasoning about backward compatibility requires an adequate semantic model to compare the behavior of two library implementations.
In the object-oriented setting with inheritance and callbacks, finding such models is difficult as the interface between library implementations and clients are complex.
Furthermore, handling these models in a way to support practical reasoning requires appropriate verification tools.
This thesis proposes a formal model for library implementations and a reasoning approach for backward compatibility that is implemented using an automatic verifier. The first part of the thesis develops a fully abstract trace-based semantics for class libraries of a core sequential object-oriented language. Traces abstract from the control flow (stack) and data representation (heap) of the library implementations. The construction of a most general context is given that abstracts exactly from all possible clients of the library implementation.
Soundness and completeness of the trace semantics as well as the most general context are proven using specialized simulation relations on the operational semantics. The simulation relations also provide a proof method for reasoning about backward compatibility.
The second part of the thesis presents the implementation of the simulation-based proof method for an automatic verifier to check backward compatibility of class libraries written in Java. The approach works for complex library implementations, with recursion and loops, in the setting of unknown program contexts. The verification process relies on a coupling invariant that describes a relation between programs that use the old library implementation and programs that use the new library implementation. The thesis presents a specification language to formulate such coupling invariants. Finally, an application of the developed theory and tool to typical examples from the literature validates the reasoning and verification approach.