### Refine

#### Year of publication

- 2018 (89) (remove)

#### Document Type

- Doctoral Thesis (51)
- Article (27)
- Conference Proceeding (5)
- Master's Thesis (3)
- Preprint (3)

#### Language

- English (89) (remove)

#### Keywords

- Visualization (3)
- Evaluation (2)
- classification (2)
- iron (2)
- machine learning (2)
- 1D-CFD (1)
- 2D-CFD (1)
- ADAS (1)
- Addukt (1)
- Algorithmic Differentiation (1)

#### Faculty / Organisational entity

- Fachbereich Informatik (18)
- Fachbereich Mathematik (18)
- Fachbereich Maschinenbau und Verfahrenstechnik (12)
- Fachbereich Biologie (11)
- Fachbereich Elektrotechnik und Informationstechnik (7)
- Fachbereich Physik (7)
- Fachbereich Sozialwissenschaften (6)
- Fachbereich Chemie (5)
- Fachbereich Wirtschaftswissenschaften (3)
- Fachbereich Raum- und Umweltplanung (2)

In this thesis, we deal with the finite group of Lie type \(F_4(2^n)\). The aim is to find information on the \(l\)-decomposition numbers of \(F_4(2^n)\) on unipotent blocks for \(l\neq2\) and \(n\in \mathbb{N}\) arbitrary and on the irreducible characters of the Sylow \(2\)-subgroup of \(F_4(2^n)\).
S. M. Goodwin, T. Le, K. Magaard and A. Paolini have found a parametrization of the irreducible characters of the unipotent subgroup \(U\) of \(F_4(q)\), a Sylow \(2\)-subgroup of \(F_4(q)\), of \(F_4(p^n)\), \(p\) a prime, for the case \(p\neq2\).
We managed to adapt their methods for the parametrization of the irreducible characters of the Sylow \(2\)-subgroup for the case \(p=2\) for the group \(F_4(q)\), \(q=p^n\). This gives a nearly complete parametrization of the irreducible characters of the unipotent subgroup \(U\) of \(F_4(q)\), namely of all irreducible characters of \(U\) arising from so-called abelian cores.
The general strategy we have applied to obtain information about the \(l\)-decomposition numbers on unipotent blocks is to induce characters of the unipotent subgroup \(U\) of \(F_4(q)\) and Harish-Chandra induce projective characters of proper Levi subgroups of \(F_4(q)\) to obtain projective characters of \(F_4(q)\). Via Brauer reciprocity, the multiplicities of the ordinary irreducible unipotent characters in these projective characters give us information on the \(l\)-decomposition numbers of the unipotent characters of \(F_4(q)\).
Sadly, the projective characters of \(F_4(q)\) we obtained were not sufficient to give the shape of the entire decomposition matrix.

The design of the fifth generation (5G) cellular network should take account of the emerging services with divergent quality of service requirements. For instance, a vehicle-to-everything (V2X) communication is required to facilitate the local data exchange and therefore improve the automation level in automated driving applications. In this work, we inspect the performance of two different air interfaces (i.e., LTE-Uu and PC5) which are proposed by the third generation partnership project (3GPP) to enable the V2X communication. With these two air interfaces, the V2X communication can be realized by transmitting data packets either over the network infrastructure or directly among traffic participants. In addition, the ultra-high reliability requirement in some V2X communication scenarios can not be fulfilled with any single transmission technology (i.e., either LTE-Uu or PC5). Therefore, we discuss how to efficiently apply multi-radio access technologies (multi-RAT) to improve the communication reliability. In order to exploit the multi-RAT in an efficient manner, both the independent and the coordinated transmission schemes are designed and inspected. Subsequently, the conventional uplink is also extended to the case where a base station can receive data packets through both the LTE-Uu and PC5 interfaces. Moreover, different multicast-broadcast single-frequency network (MBSFN) area mapping approaches are also proposed to improve the communication reliability in the LTE downlink. Last but not least, a system level simulator is implemented in this work. The simulation results do not only provide us insights on the performances of different technologies but also validate the effectiveness of the proposed multi-RAT scheme.

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.

Motivation: Mathematical models take an important place in science and engineering.
A model can help scientists to explain dynamic behavior of a system and to understand
the functionality of system components. Since length of a time series and number of
replicates is limited by the cost of experiments, Boolean networks as a structurally simple
and parameter-free logical model for gene regulatory networks have attracted interests
of many scientists. In order to fit into the biological contexts and to lower the data
requirements, biological prior knowledge is taken into consideration during the inference
procedure. In the literature, the existing identification approaches can only deal with a
subset of possible types of prior knowledge.
Results: We propose a new approach to identify Boolean networks fromtime series data
incorporating prior knowledge, such as partial network structure, canalizing property,
positive and negative unateness. Using vector form of Boolean variables and applying
a generalized matrix multiplication called the semi-tensor product (STP), each Boolean
function can be equivalently converted into a matrix expression. Based on this, the
identification problem is reformulated as an integer linear programming problem to
reveal the system matrix of Boolean model in a computationally efficient way, whose
dynamics are consistent with the important dynamics captured in the data. By using
prior knowledge the number of candidate functions can be reduced during the inference.
Hence, identification incorporating prior knowledge is especially suitable for the case of
small size time series data and data without sufficient stimuli. The proposed approach is
illustrated with the help of a biological model of the network of oxidative stress response.
Conclusions: The combination of efficient reformulation of the identification problem
with the possibility to incorporate various types of prior knowledge enables the
application of computational model inference to systems with limited amount of time
series data. The general applicability of thismethodological approachmakes it suitable for
a variety of biological systems and of general interest for biological and medical research.

The core muscles play a central role in stabilizing the head during headers in soccer. The objective of this study was to examine the influence of a fatigued core musculature on the acceleration of the head during jump headers and run headers. Acceleration of the head was measured in a pre-post-design in 68 soccer players (age: 21.5 ± 3.8 years, height: 180.0 ± 13.9 cm, weight: 76.9 ± 8.1 kg). Data were recorded by means of a telemetric 3D acceleration sensor and with a pendulum header. The treatment encompassed two exercises each for the ventral, lateral, and dorsal muscle chains. The acceleration of the head between pre- and post-test was reduced by 0.3 G (p = 0.011) in jump headers and by 0.2 G (p = 0.067) in run headers. An additional analysis of all pretests showed an increased acceleration in run headers when compared to stand headers (p < 0.001) and jump headers (p < 0.001). No differences were found in the sub-group comparisons: semi-professional vs. recreational players, offensive vs. defensive players. Based on the results, we conclude that the acceleration of the head after fatiguing the core muscles does not increase, which stands in contrast to postulated expectations. More tests with accelerated soccer balls are required for a conclusive statement.

The complexity of modern real-time systems is increasing day by day. This inevitable rise in complexity predominantly stems from two contradicting requirements, i.e., ever increasing demand for functionality, and required low cost for the final product. The development of modern multi-processors and variety of network protocols and architectures have enabled such a leap in complexity and functionality possible. Albeit, efficient use of these multi-processors and network architectures is still a major problem. Moreover, the software design and its development process needs improvements in order to support rapid-prototyping for ever changing system designs. Therefore, in this dissertation, we provide solutions for different problems faced in the development and deployment process of real-time systems. The contributions presented in this thesis enable efficient utilization of system resources, rapid design & development and component modularity & portability.
In order to ease the certification process, time-triggered computation model is often used in distributed systems. However, time-triggered scheduling is NP-hard, due to which the process of schedule generation for complex large systems becomes convoluted. Large scheduler run-times and low scalability are two major problems with time-triggered scheduling. To solve these problems, we present a modular real-time scheduler based on a novel search-tree pruning technique, which consumes less time (compared to the state-of-the-art) in order to schedule tasks on large distributed time-triggered systems. In order to provide end-to-end guarantees, we also extend our modular scheduler to quickly generate schedules for time-triggered network traffic in large TTEthernet based networks. We evaluate our schedulers on synthetic but practical task-sets and demonstrate that our pruning technique efficiently reduces scheduler run-times and exhibits adequate scalability for future time-triggered distributed systems.
In safety critical systems, the certification process also requires strict isolation between independent components. This isolation is enforced by utilizing resource partitioning approach, where different criticality components execute in different partitions (each temporally and spatially isolated from each other). However, existing partitioning approaches use periodic servers or tasks to service aperiodic activities. This approach leads to utilization loss and potentially leads to large latencies. On the contrary to the periodic approaches, state-of-the-art aperiodic task admission algorithms do not suffer from problems like utilization loss. However, these approaches do not support partitioned scheduling or mixed-criticality execution environment. To solve this problem, we propose an algorithm for online admission of aperiodic tasks which provides job execution flexibility, jitter control and leads to lower latencies of aperiodic tasks.
For safety critical systems, fault-tolerance is one of the most important requirements. In time-triggered systems, modes are often used to ensure survivability against faults, i.e., when a fault is detected, current system configuration (or mode) is changed such that the overall system performance is either unaffected or degrades gracefully. In literature, it has been asserted that a task-set might be schedulable in individual modes but unschedulable during a mode-change. Moreover, conventional mode-change execution strategies might cause significant delays until the next mode is established. In order to address these issues, in this dissertation, we present an approach for schedulability analysis of mode-changes and propose mode-change delay reduction techniques in distributed system architecture defined by the DREAMS project. We evaluate our approach on an avionics use case and demonstrate that our approach can drastically reduce mode-change delays.
In order to manage increasing system complexity, real-time applications also require new design and development technologies. Other than fulfilling the technical requirements, the main features required from such technologies include modularity and re-usability. AUTOSAR is one of these technologies in automotive industry, which defines an open standard for software architecture of a real-time operating system. However, being an industrial standard, the available proprietary tools do not support model extensions and/or new developments by third-parties and, therefore, hinder the software evolution. To solve this problem, we developed an open-source AUTOSAR toolchain which supports application development and code generation for several modules. In order to exhibit the capabilities of our toolchain, we developed two case studies. These case studies demonstrate that our toolchain generates valid artifacts, avoids dirty workarounds and supports application development.
In order to cope with evolving system designs and hardware platforms, rapid-development of scheduling and analysis algorithms is required. In order to ease the process of algorithm development, a number of scheduling and analysis frameworks are proposed in literature. However, these frameworks focus on a specific class of applications and are limited in functionality. In this dissertation, we provide the skeleton of a scheduling and analysis framework for real-time systems. In order to support rapid-development, we also highlight different development components which promote code reuse and component modularity.

Arctic, Antarctic and alpine biological soil crusts (BSCs) are formed by adhesion of soil particles to exopolysaccharides (EPSs) excreted by cyanobacterial and green algal communities, the pioneers and main primary producers in these habitats. These BSCs provide and inﬂuence many ecosystem services such as soil erodibility, soil formation and nitrogen (N) and carbon (C) cycles. In cold environments degradation rates are low and BSCs continuously increase soil organic C; therefore, these soils are considered to be CO2 sinks. This work provides a novel, nondestructive and highly comparable method to investigate intact BSCs with a focus on cyanobacteria and green algae and their contribution to soil organic C. A new terminology arose,basedonconfocallaserscanningmicroscopy(CLSM) 2-D biomaps, dividing BSCs into a photosynthetic active layer (PAL) made of active photoautotrophic organisms and a photosynthetic inactive layer (PIL) harbouring remnants of cyanobacteria and green algae glued together by their remaining EPSs. By the application of CLSM image analysis (CLSM–IA) to 3-D biomaps, C coming from photosynthetic activeorganismscouldbevisualizedasdepthproﬁleswithC peaks at 0.5 to 2mm depth. Additionally, the CO2 sink character of these cold soil habitats dominated by BSCs could be highlighted, demonstrating that the ﬁrst cubic centimetre of soil consists of between 7 and 17% total organic carbon, identiﬁed by loss on ignition.

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.

A fast numerical method for an advanced electro-chemo-mechanical model is developed which is able to capture phase separation processes in porous materials. This method is applied to simulate lithium-ion battery cells, where the complex microstructure of the electrodes is fully resolved. The intercalation of ions into the popular cathode material LFP leads to a separation into lithium-rich and lithium-poor phases. The large concentration gradients result in high mechanical stresses. A phase-field method applying the Cahn-Hilliard equation is used to describe the diffusion. For the sake of simplicity, the linear elastic case is considered. Numerical tests for fully resolved three-dimensional granular microstructures are discussed in detail.

The Power and Energy Student Summit (PESS) is designed for students, young professionals and PhD-students in the field of power engineering. PESS offers the possibility to gain first experience in presentation, publication and discussion with a renowned audience of specialists. Therefore, the conference is accompanied and supervised by established scientists and experts. The venue changes every year. In 2018, the University of Kaiserslautern held the eighth PESS conference. This document presents the submissions of this conference.

Ecophysiological characterizations of photoautotrophic communities are not only necessary to identify the response of carbon fixation related to different climatic factors, but also to evaluate risks connected to changing environments. In biological soil crusts (BSCs), the description of ecophysiological features is difficult, due to the high variability in taxonomic composition and variable methodologies applied. Especially for BSCs in early successional stages, the available datasets are rare or focused on individual constituents, although these crusts may represent the only photoautotrophic component in many heavily disturbed ruderal areas, such as parking lots or building areas with increasing surface area worldwide. We analyzed the response of photosynthesis and respiration to changing BSC water contents (WCs), temperature and light in two early successional BSCs. We investigated whether the response of these parameters was different between intact BSC and the isolated dominating components. BSCs dominated by the cyanobacterium Nostoc commune and dominated by the green alga Zygogonium ericetorum were examined. A major divergence between the two BSCs was their absolute carbon fixation rate on a chlorophyll basis, which was significantly higher for the cyanobacterial crust. Nevertheless, independent of species composition, both crust types and their isolated organisms had convergent features such as high light acclimatization and a minor and very late-occurring depression in carbon uptake at water suprasaturation. This particular setup of ecophysiological features may enable these communities to cope with a high variety of climatic stresses and may therefore be a reason for their success in heavily disturbed areas with ongoing human impact. However, the shape of the response was different for intact BSC compared to separated organisms, especially in absolute net photosynthesis (NP) rates. This emphasizes the importance of measuring intact BSCs under natural conditions for collecting reliable data for meaningful analysis of BSC ecosystem services.

Background: Aneuploidy, or abnormal chromosome numbers, severely alters cell physiology and is widespread in
cancers and other pathologies. Using model cell lines engineered to carry one or more extra chromosomes, it has
been demonstrated that aneuploidy per se impairs proliferation, leads to proteotoxic as well as replication stress
and triggers conserved transcriptome and proteome changes.
Results: In this study, we analysed for the first time miRNAs and demonstrate that their expression is altered in
response to chromosome gain. The miRNA deregulation is independent of the identity of the extra chromosome
and specific to individual cell lines. By cross-omics analysis we demonstrate that although the deregulated miRNAs
differ among individual aneuploid cell lines, their known targets are predominantly associated with cell development,
growth and proliferation, pathways known to be inhibited in response to chromosome gain. Indeed, we show that up
to 72% of these targets are downregulated and the associated miRNAs are overexpressed in aneuploid cells, suggesting
that the miRNA changes contribute to the global transcription changes triggered by aneuploidy. We identified
hsa-miR-10a-5p to be overexpressed in majority of aneuploid cells. Hsa-miR-10a-5p enhances translation of a
subset of mRNAs that contain so called 5’TOP motif and we show that its upregulation in aneuploids provides
resistance to starvation-induced shut down of ribosomal protein translation.
Conclusions: Our work suggests that the changes of the microRNAome contribute on one hand to the adverse
effects of aneuploidy on cell physiology, and on the other hand to the adaptation to aneuploidy by supporting
translation under adverse conditions.
Keywords: Aneuploidy, Cancer, miRNA, miR-10a-5p, Trisomy

Areal optical surface topography measurement is an emerging technology for industrial quality control. However, neither calibration procedures nor the utilization of material measures are standardized. State of the art is the calibration of a set of metrological characteristics with multiple calibration samples (material measures). Here, we propose a new calibration sample (artefact) capable of providing the entire set of relevant metrological characteristics within only one single sample. Our calibration artefact features multiple material measures and is manufactured with two-photon laser lithography (direct laser writing, DLW). This enables a holistic calibration of areal topography measuring instruments with only one series of measurements and without changing the sample.

Based on the Lindblad master equation approach we obtain a detailed microscopic model of photons in a dye-filled cavity, which features condensation of light. To this end we generalise a recent non-equilibrium approach of Kirton and Keeling such that the dye-mediated contribution to the photon-photon interaction in the light condensate is accessible due to an interplay of coherent and dissipative dynamics. We describe the steady-state properties of the system by analysing the resulting equations of motion of both photonic and matter degrees of freedom. In particular, we discuss the existence of two limiting cases for steady states: photon Bose-Einstein condensate and laser-like. In the former case, we determine the corresponding dimensionless photon-photon interaction strength by relying on realistic experimental data and find a good agreement with previous theoretical estimates. Furthermore, we investigate how the dimensionless interaction strength depends on the respective system parameters.

We studied the development of cognitive abilities related to intelligence and creativity
(N = 48, 6–10 years old), using a longitudinal design (over one school year), in order
to evaluate an Enrichment Program for gifted primary school children initiated by
the government of the German federal state of Rhineland-Palatinate (Entdeckertag
Rheinland Pfalz, Germany; ET; Day of Discoverers). A group of German primary school
children (N = 24), identified earlier as intellectually gifted and selected to join the
ET program was compared to a gender-, class- and IQ- matched group of control
children that did not participate in this program. All participants performed the Standard
Progressive Matrices (SPM) test, which measures intelligence in well-defined problem
space; the Creative Reasoning Task (CRT), which measures intelligence in ill-defined
problem space; and the test of creative thinking-drawing production (TCT-DP), which
measures creativity, also in ill-defined problem space. Results revealed that problem
space matters: the ET program is effective only for the improvement of intelligence
operating in well-defined problem space. An effect was found for intelligence as
measured by SPM only, but neither for intelligence operating in ill-defined problem space
(CRT) nor for creativity (TCT-DP). This suggests that, depending on the type of problem
spaces presented, different cognitive abilities are elicited in the same child. Therefore,
enrichment programs for gifted, but also for children attending traditional schools,
should provide opportunities to develop cognitive abilities related to intelligence,
operating in both well- and ill-defined problem spaces, and to creativity in a parallel,
using an interactive approach.

Composite materials are used in many modern tools and engineering applications and
consist of two or more materials that are intermixed. Features like inclusions in a matrix
material are often very small compared to the overall structure. Volume elements that
are characteristic for the microstructure can be simulated and their elastic properties are
then used as a homogeneous material on the macroscopic scale.
Moulinec and Suquet [2] solve the so-called Lippmann-Schwinger equation, a reformulation of the equations of elasticity in periodic homogenization, using truncated
trigonometric polynomials on a tensor product grid as ansatz functions.
In this thesis, we generalize their approach to anisotropic lattices and extend it to
anisotropic translation invariant spaces. We discretize the partial differential equation
on these spaces and prove the convergence rate. The speed of convergence depends on
the smoothness of the coefficients and the regularity of the ansatz space. The spaces of
translates unify the ansatz of Moulinec and Suquet with de la Vallée Poussin means and
periodic Box splines, including the constant finite element discretization of Brisard and
Dormieux [1].
For finely resolved images, sampling on a coarser lattice reduces the computational
effort. We introduce mixing rules as the means to transfer fine-grid information to the
smaller lattice.
Finally, we show the effect of the anisotropic pattern, the space of translates, and the
convergence of the method, and mixing rules on two- and three-dimensional examples.
References
[1] S. Brisard and L. Dormieux. “FFT-based methods for the mechanics of composites:
A general variational framework”. In: Computational Materials Science 49.3 (2010),
pp. 663–671. doi: 10.1016/j.commatsci.2010.06.009.
[2] H. Moulinec and P. Suquet. “A numerical method for computing the overall response
of nonlinear composites with complex microstructure”. In: Computer Methods in
Applied Mechanics and Engineering 157.1-2 (1998), pp. 69–94. doi: 10.1016/s00457825(97)00218-1.

Field-effect transistor (FET) sensors and in particular their nanoscale variant of silicon nanowire transistors are very promising technology platforms for label-free biosensor applications. These devices directly detect the intrinsic electrical charge of biomolecules at the sensor’s liquid-solid interface. The maturity of micro fabrication techniques enables very large FET sensor arrays for massive multiplex detection. However, the direct detection of charged molecules in liquids faces a significant limitation due to a charge screening effect in physiological solutions, which inhibits the realization of point-of-care applications. As an alternative, impedance spectroscopy with FET devices has the potential to enable measurements in physiological samples. Even though promising studies were published in the field, impedimetric detection with silicon FET devices is not well understood.
The first goal of this thesis was to understand the device performances and to relate the effects seen in biosensing experiments to device and biomolecule types. A model approach should help to understand the capability and limitations of the impedimetric measurement method with FET biosensors. In addition, to obtain experimental results, a high precision readout device was needed. Consequently, the second goal was to build up multi-channel, highly accurate amplifier systems that would also enable future multi-parameter handheld devices.
A PSPICE FET model for potentiometric and impedimetric detection was adapted to the experiments and further expanded to investigate the sensing mechanism, the working principle, and effects of side parameters for the biosensor experiments. For potentiometric experiments, the pH sensitivity of the sensors was also included in this modelling approach. For impedimetric experiments, solutions of different conductivity were used to validate the suggested theories and assumptions. The impedance spectra showed two pronounced frequency domains: a low-pass characteristic at lower frequencies and a resonance effect at higher frequencies. The former can be interpreted as a contribution of the source and double layer capacitances. The latter can be interpreted as a combined effect of the drain capacitance with the operational amplifier in the transimpedance circuit.
Two readout systems, one as a laboratory system and one as a point-of-care demonstrator, were developed and used for several chemical and biosensing experiments. The PSPICE model applied to the sensors and circuits were utilized to optimize the systems and to explain the sensor responses. The systems as well as the developed modelling approach were a significant step towards portable instruments with combined transducer principles in future healthcare applications.

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 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.

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

The authors explore the intrinsic trade-off in a DRAM between the power consumption (due to refresh) and the reliability. Their unique measurement platform allows tailoring to the design constraints depending on whether power consumption, performance or reliability has the highest design priority. Furthermore, the authors show how this measurement platform can be used for reverse engineering the internal structure of DRAMs and how this knowledge can be used to improve DRAM’s reliability.

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

Autonomous driving is disrupting the conventional automotive development. In fact, autonomous driving kicks off the consolidation of control units, i.e. the transition from distributed Electronic Control Units (ECUs) to centralized domain controllers. Platforms like Audi’s zFAS demonstrate this very clearly, where GPUs, Custom SoCs, Microcontrollers, and FPGAs are integrated on a single domain controller in order to perform sensor fusion, processing and decision making on a single Printed Circuit Board (PCB). The communication between these heterogeneous components and the algorithms for Advanced Driving Assistant Systems (ADAS) itself requires a huge amount of memory bandwidth, which will bring the Memory Wall from High Performance Computing (HPC) and data-centers directly in our cars. In this paper we highlight the roles and issues of Dynamic Random Access Memories (DRAMs) for future autonomous driving architectures.

In the present master’s thesis we investigate the connection between derivations and
homogeneities of complete analytic algebras. We prove a theorem, which describes a specific set of generators
for the module of derivations of an analytic algebra, which map the maximal ideal of R into itself. It turns out, that this set has a structure similar to a Cartan subalgebra and contains
information regarding multi-homogeneity. In order to prove
this theorem, we extend the notion of grading by Scheja and Wiebe to projective systems and state the connection between multi-gradings and pairwise
commuting diagonalizable derivations. We prove a theorem similar to Cartan’s Conjugacy Theorem in the setup of infinite-dimensional Lie algebras, which arise as projective limits of finite-dimensional Lie algebras. Using this result, we can show that the structure of the aforementioned set of generators is an intrinsic property of the analytic algebra. At the end we state an algorithm, which is theoretically able to compute the maximal multi-homogeneity of a complete analytic algebra.

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.

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.

Benzene is a natural constituent of crude oil and a product of incomplete combustion of petrol
and has been classified as “carcinogenic to humans” by IARC in 1982 (IARC 1982). (E,E)-
Muconaldehyde has been postulated to be a microsomal metabolite of benzene in vitro
(Latriano et al. 1986). (E,E)-Muconaldehyde is hematotoxic in vivo and its role in the
hematotoxicity of benzene is unclear (Witz et al. 1985).
We intended to ascertain the presence of (E,E)-muconaldehyde in vivo by detection of a
protein conjugate deriving from (E,E)-muconaldehyde.
Therefore we improved the current synthetic access to (E,E)-muconaldehyde. (E,E)-
muconaldehyde was synthesized in three steps starting from with (E,E)-muconic acid in an
overall yield of 60 %.
Reaction of (E,E)-muconaldehyde with bovine serum albumin resulted in formation of a
conjugate which was converted upon addition of NaBH4 to a new species whose HPLC-
retention time, UV spectra, Q1 mass and MS2 spectra matched those of the crude reaction
product from one pot conversion of Ac-Lys-OMe with (E,E)-muconaldehyde in the presence
of NaBH4 and subsequent cleavage of protection groups.
Synthetic access to the presumed structure (S)-2-ammonio-6-(((E,E)-6-oxohexa-2,4-dien-1-
yl)amino)hexanoate (Lys(MUC-CHO)) was provided in eleven steps starting from (E,E)-
muconic acid and Lys(Z)-OtBu*HCl in 2 % overall yield. Additionally synthetic access to
(S)-2-ammonio-6-(((E,E)-6-hydroxyhexa-2,4-dien-1-yl)amino)hexanoate (Lys(MUC-OH))
and (S)-2-ammonio-6-((6-hydroxyhexyl)amino)hexanoate (IS) was provided.
With synthetic reference material at hand, the presumed structure Lys(MUC-OH) could be
identified from incubations of (E,E)-muconaldehyde with bovine serum albumin via HPLC-ESI+-
MS/MS.
Cytotoxicity analysis of (E,E)-muconaldehyde and Lys(MUC-CHO) in human promyelocytic
NB4 cells resulted in EC50 ≈ 1 μM for (E,E)-muconaldehyde. Lys(MUC-CHO) did not show
any additional cytotoxicity up to 10 μM.
B6C3F1 mice were exposed to 0, 400 and 800 mg/kg b.w. benzene to examine the formation
of Lys(MUC-OH) in vivo. After 24 h mice were sacrificed and serum albumin was isolated.
Analysis for Lys(MUC-OH) has not been performed in this work.

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

Using valuation theory we associate to a one-dimensional equidimensional semilocal Cohen-Macaulay ring \(R\) its semigroup of values, and to a fractional ideal of \(R\) we associate its value semigroup ideal. For a class of curve singularities (here called admissible rings) including algebroid curves the semigroups of values, respectively the value semigroup ideals, satisfy combinatorial properties defining good semigroups, respectively good semigroup ideals. Notably, the class of good semigroups strictly contains the class of value semigroups of admissible rings. On good semigroups we establish combinatorial versions of algebraic concepts on admissible rings which are compatible with their prototypes under taking values. Primarily we examine duality and quasihomogeneity.
We give a definition for canonical semigroup ideals of good semigroups which characterizes canonical fractional ideals of an admissible ring in terms of their value semigroup ideals. Moreover, a canonical semigroup ideal induces a duality on the set of good semigroup ideals of a good semigroup. This duality is compatible with the Cohen-Macaulay duality on fractional ideals under taking values.
The properties of the semigroup of values of a quasihomogeneous curve singularity lead to a notion of quasihomogeneity on good semigroups which is compatible with its algebraic prototype. We give a combinatorial criterion which allows to construct from a quasihomogeneous semigroup \(S\) a quasihomogeneous curve singularity having \(S\) as semigroup of values.
As an application we use the semigroup of values to compute endomorphism rings of maximal ideals of algebroid curves. This yields an explicit description of the intermediate rings in an algorithmic normalization of plane central arrangements of smooth curves based on a criterion by Grauert and Remmert. Applying this result to hyperplane arrangements we determine the number of steps needed to compute the normalization of a the arrangement in terms of its Möbius function.

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.

Multiphase materials combine properties of several materials, which makes them interesting for high-performing components. This thesis considers a certain set of multiphase materials, namely silicon-carbide (SiC) particle-reinforced aluminium (Al) metal matrix composites and their modelling based on stochastic geometry models.
Stochastic modelling can be used for the generation of virtual material samples: Once we have fitted a model to the material statistics, we can obtain independent three-dimensional “samples” of the material under investigation without the need of any actual imaging. Additionally, by changing the model parameters, we can easily simulate a new material composition.
The materials under investigation have a rather complicated microstructure, as the system of SiC particles has many degrees of freedom: Size, shape, orientation and spatial distribution. Based on FIB-SEM images, that yield three-dimensional image data, we extract the SiC particle structure using methods of image analysis. Then we model the SiC particles by anisotropically rescaled cells of a random Laguerre tessellation that was fitted to the shapes of isotropically rescaled particles. We fit a log-normal distribution for the volume distribution of the SiC particles. Additionally, we propose models for the Al grain structure and the Aluminium-Copper (\({Al}_2{Cu}\)) precipitations occurring on the grain boundaries and on SiC-Al phase boundaries.
Finally, we show how we can estimate the parameters of the volume-distribution based on two-dimensional SEM images. This estimation is applied to two samples with different mean SiC particle diameters and to a random section through the model. The stereological estimations are within acceptable agreement with the parameters estimated from three-dimensional image data
as well as with the parameters of the model.

Epoxy belongs to a category of high-performance thermosetting polymers which have been used extensively in industrial and consumer applications. Highly cross-linked epoxy polymers offer excellent mechanical properties, adhesion, and chemical resistance. However, unmodified epoxies are prone to brittle fracture and crack propagation due to their highly crosslinked structure. As a result, epoxies are normally toughened to ensure the usability of these materials in practical applications.
This research work focuses on the development of novel modified epoxy matrices, with enhanced mechanical, fracture mechanical and thermal properties, suitable to be processed by filament winding technology, to manufacture composite based calender roller covers with improved performance in comparison to commercially available products.
In the first stage, a neat epoxy resin (EP) was modified using three different high functionality epoxy resins with two type of hardeners i.e. amine-based (H1) and anhydride-based (H2). Series of hybrid epoxy resins were obtained by systematic variation of high functionality epoxy resin contents with reference epoxy system. The resulting matrices were characterized by their tensile properties and the best system was chosen from each hardener system i.e. amine and anhydride. For tailored amine based system (MEP_H1) 14 % improvement was measured for bulk samples similarly, for tailored anhydride system (MEP_H2) 11 % improvement was measured when tested at 23 °C.
Further, tailored epoxy systems (MEP_H1 and MEP_H2) were modified using specially designed block copolymer (BCP), and core-shell rubber nanoparticles (CSR). Series of nanocomposites were obtained by systematic variation of filler contents. The resulting matrices were extensively characterized qualitatively and quantitatively to reveal the effect of each filler on the polymer properties. It was shown that the BCP confer better fracture properties to the epoxy resin at low filler loading without losing the other mechanical properties. These characteristics were accompanied by ductility and temperature stability. All composites were tested at 23 °C and at 80 °C to understand the effect of temperature on the mechanical and fracture properties.
Examinations on fractured specimen surfaces provided information about the mechanisms responsible for reinforcement. Nanoparticles generate several energy dissipating mechanisms in the epoxy, e.g. plastic deformation of the matrix, cavitation, void growth, debonding and crack pinning. These were closely related to the microstructure of the materials. The characteristic of the microstructure was verified by microscopy methods (SEM and AFM). The microstructure of neat epoxy hardener system was strongly influenced by the nanoparticles and the resulting interfacial interactions. The interaction of nanoparticles with a different hardener system will result in different morphology which will ultimately influence the mechanical and fracture mechanical properties of the nanocomposites. Hybrid toughening using a combination of the block-copolymer / core-shell rubber nanoparticles and block copolymer / TiO2 nanoparticles has been investigated in the epoxy systems. It was found out that addition of rigid phase with a soft phase recovers the loss of strength in the nanocomposites caused by a softer phase.
In order to clarify the relevant relationships, the microstructural and mechanical properties were correlated. The Counto’s, Halpin-Tsai, and Lewis-Nielsen equations were used to calculate the modulus of the composites and predicted modulus fit well with the measured values. Modeling was done to predict the toughening contribution from block copolymers and core-shell rubber nanoparticles. There was good agreement between the predicted values and the experimental values for the fracture energy.

Embedded reactive systems underpin various safety-critical applications wherein they interact with other systems and the environment with limited or even no human supervision. Therefore, design errors that violate essential system specifications can lead to severe unacceptable damages. For this reason, formal verification of such systems in their physical environment is of high interest. Synchronous programs are typically used to represent embedded reactive systems while hybrid systems serve to model discrete reactive system in a continuous environment. As such, both synchronous programs and hybrid systems play important roles in the model-based design of embedded reactive systems. This thesis develops induction-based techniques for safety property verification of synchronous and hybrid programs. The imperative synchronous language Quartz and its hybrid systems’ extensions are used to sustain the findings.
Deductive techniques for software verification typically use Hoare calculus. In this context, Verification Condition Generation (VCG) is used to apply Hoare calculus rules to a program whose statements are annotated with pre- and postconditions so that the validity of an obtained Verification Condition (VC) implies correctness of a given proof goal. Due to the abstraction of macro steps, Hoare calculus cannot directly generate VCs of synchronous programs unless it handles additional label variables or goto statements. As a first contribution, Floyd’s induction-based approach is employed to generate VCs for synchronous and hybrid programs. Five VCG methods are introduced that use inductive assertions to decompose the overall proof goal. Given the right assertions, the procedure can automatically generate a set of VCs that can then be checked by SMT solvers or automated theorem provers. The methods are proved sound and relatively complete, provided that the underlying assertion language is expressive enough. They can be applied to any program with a state-based semantics.
Property Directed Reachability (PDR) is an efficient method for synchronous hardware circuit verification based on induction rather than fixpoint computation. Crucial steps of the PDR method consist of deciding about the reachability of Counterexamples to Induction (CTIs) and generalizing them to clauses that cover as many unreachable states as possible. The thesis demonstrates that PDR becomes more efficient for imperative synchronous programs when using the distinction between the control- and dataflow. Before calling the PDR method, it is possible to derive additional program control-flow information that can be added to the transition relation such that less CTIs will be generated. Two methods to compute additional control-flow information are presented that differ in how precisely they approximate the reachable control-flow states and, consequently, in their required runtime. After calling the PDR method, the CTI identification work is reduced to its control-flow part and to checking whether the obtained control-flow states are unreachable in the corresponding extended finite state machine of the program. If so, all states of the transition system that refer to the same program locations can be excluded, which significantly increases the performance of PDR.

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.

Multifacility location problems arise in many real world applications. Often, the facilities can only be placed in feasible regions such as development or industrial areas. In this paper we show the existence of a finite dominating set (FDS) for the planar multifacility location problem with polyhedral gauges as distance functions, and polyhedral feasible regions, if the interacting facilities form a tree. As application we show how to solve the planar 2-hub location problem in polynomial time. This approach will yield an ε-approximation for the euclidean norm case polynomial in the input data and 1/ε.

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.

A popular model for the locations of fibres or grains in composite materials
is the inhomogeneous Poisson process in dimension 3. Its local intensity function
may be estimated non-parametrically by local smoothing, e.g. by kernel
estimates. They crucially depend on the choice of bandwidths as tuning parameters
controlling the smoothness of the resulting function estimate. In this
thesis, we propose a fast algorithm for learning suitable global and local bandwidths
from the data. It is well-known, that intensity estimation is closely
related to probability density estimation. As a by-product of our study, we
show that the difference is asymptotically negligible regarding the choice of
good bandwidths, and, hence, we focus on density estimation.
There are quite a number of data-driven bandwidth selection methods for
kernel density estimates. cross-validation is a popular one and frequently proposed
to estimate the optimal bandwidth. However, if the sample size is very
large, it becomes computational expensive. In material science, in particular,
it is very common to have several thousand up to several million points.
Another type of bandwidth selection is a solve-the-equation plug-in approach
which involves replacing the unknown quantities in the asymptotically optimal
bandwidth formula by their estimates.
In this thesis, we develop such an iterative fast plug-in algorithm for estimating
the optimal global and local bandwidth for density and intensity estimation with a focus on 2- and 3-dimensional data. It is based on a detailed
asymptotics of the estimators of the intensity function and of its second
derivatives and integrals of second derivatives which appear in the formulae
for asymptotically optimal bandwidths. These asymptotics are utilised to determine
the exact number of iteration steps and some tuning parameters. For
both global and local case, fewer than 10 iterations suffice. Simulation studies
show that the estimated intensity by local bandwidth can better indicate
the variation of local intensity than that by global bandwidth. Finally, the
algorithm is applied to two real data sets from test bodies of fibre-reinforced
high-performance concrete, clearly showing some inhomogeneity of the fibre
intensity.

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.

Crowd condition monitoring concerns the crowd safety and concerns business performance metrics. The research problem to be solved is a crowd condition estimation approach to enable and support the supervision of mass events by first-responders and marketing experts, but is also targeted towards supporting social scientists, journalists, historians, public relations experts, community leaders, and political researchers. Real-time insights of the crowd condition is desired for quick reactions and historic crowd conditions measurements are desired for profound post-event crowd condition analysis.
This thesis aims to provide a systematic understanding of different approaches for crowd condition estimation by relying on 2.4 GHz signals and its variation in crowds of people, proposes and categorizes possible sensing approaches, applies supervised machine learning algorithms, and demonstrates experimental evaluation results. I categorize four sensing approaches. Firstly, stationary sensors which are sensing crowd centric signals sources. Secondly, stationary sensors which are sensing other stationary signals sources (either opportunistic or special purpose signal sources). Thirdly, a few volunteers within the crowd equipped with sensors which are sensing other surrounding crowd centric device signals (either individually, in a single group or collaboratively) within a small region. Fourthly, a small subset of participants within the crowd equipped with sensors and roaming throughout a whole city to sense wireless crowd centric signals.
I present and evaluate an approach with meshed stationary sensors which were sensing crowd centric devices. This was demonstrated and empirically evaluated within an industrial project during three of the world-wide largest automotive exhibitions. With over 30 meshed stationary sensors in an optimized setup across 6400m2 I achieved a mean absolute error of the crowd density of just 0.0115
people per square meter which equals to an average of below 6% mean relative error from the ground truth. I validate the contextual crowd condition anomaly detection method during the visit of chancellor Mrs. Merkel and during a large press conference during the exhibition. I present the approach of opportunistically sensing stationary based wireless signal variations and validate this during the Hannover CeBIT exhibition with 80 opportunistic sources with a crowd condition estimation relative error of below 12% relying only on surrounding signals in influenced by humans. Pursuing this approach I present an approach with dedicated signal sources and sensors to estimate the condition of shared office environments. I demonstrate methods being viable to even detect low density static crowds, such as people sitting at their desks, and evaluate this on an eight person office scenario. I present the approach of mobile crowd density estimation by a group of sensors detecting other crowd centric devices in the proximity with a classification accuracy of the crowd density of 66 % (improvement of over 22% over a individual sensor) during the crowded Oktoberfest event. I propose a collaborative mobile sensing approach which makes the system more robust against variations that may result from the background of the people rather than the crowd condition with differential features taking information about the link structure between actively scanning devices, the ratio between values observed by different devices, ratio of discovered crowd devices over time, team-wise diversity of discovered devices, number of semi- continuous device visibility periods, and device visibility durations into account. I validate the approach on multiple experiments including the Kaiserslautern European soccer championship public viewing event and evaluated the collaborative mobile sensing approach with a crowd condition estimation accuracy of 77 % while outperforming previous methods by 21%. I present the feasibility of deploying the wireless crowd condition sensing approach to a citywide scale during an event in Zurich with 971 actively sensing participants and outperformed the reference method by 24% in average.

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.

In this paper, we demonstrate the power of functional data models for a statistical analysis of stimulus-response experiments which is a quite natural way to look at this kind of data and which makes use of the full information available. In particular, we focus on the detection of a change in the mean of the response in a series of stimulus-response curves where we also take into account dependence in time.

In this article a new numerical solver for simulations of district heating networks is presented. The numerical method applies the local time stepping introduced in [11] to networks of linear advection equations. In combination with the high order approach of [4] an accurate and very efficient scheme is developed. In several numerical test cases the advantages for simulations of district heating networks are shown.

The screening of metagenomic datasets led to the identification of new phage-derived members of the heme oxygenase and the ferredoxin-dependent bilin reductase enzyme families.
The novel bilin biosynthesis genes were shown to form mini-cassettes on metagenomic scaffolds and further form distinct clusters in phylogenetic analyses (Ledermann et al., 2016). In this project, it was demonstrated that the discovered sequences actually encode for active enzymes. The biochemical characterization of a member of the heme oxygenases (ΦHemO) revealed that it possesses a regiospecificity for the α-methine bridge in the cleavage of the heme macrocycle. The reaction product biliverdin IXα was shown to function as the substrate for the novel ferredoxin-dependent bilin reductases (PcyX reductases), which catalyze its reduction to PEB via the intermediate 15,16-DHBV. While it was demonstrated that ΦPcyX, a phage-derived member of the PcyX reductases, is an active enzyme, it also became clear that the rate of the reaction is highly dependent on the employed redox partner. It turned out that the ferredoxin from the cyanophage P-SSM2 is to date the most suitable redox partner for the reductases of the PcyX group. Furthermore, the solution of the ΦPcyX crystal structure revealed that it adopts an α/β/α-sandwich fold, typical for the FDBR-family. Activity assays and subsequent HPLC analyses with different variants of the ΦPcyX protein demonstrated that, despite their similarity, PcyX and PcyA reductases must act via different reaction mechanisms.
Another part of this project focused on the biochemical characterization of the FDBR KflaHY2 from the streptophyte alga Klebsormidium flaccidum. Experiments with recombinant KflaHY2 showed that it is an active FDBR which produces 3(Z)-PCB as the main reaction product, like it can be found in reductases of the PcyA group. Moreover, it was shown that under the employed assay conditions the reaction of BV to PCB proceeds in two different ways: Both 3(Z)-PΦB and 18¹,18²-DHBV occur as intermediates. Activity assays with the purified intermediates yielded PCB. Hence, both compounds are suitable substrates for KflaHY2.
The results of this work highlight the importance of the biochemical experiments, as catalytic activity cannot solely be predicted by sequence analysis.

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.

The growing computational power enables the establishment of the Population Balance Equation (PBE)
to model the steady state and dynamic behavior of multiphase flow unit operations. Accordingly, the twophase
flow
behavior inside liquid-liquid extraction equipment is characterized by different factors. These
factors include: interactions among droplets (breakage and coalescence), different time scales due to the
size distribution of the dispersed phase, and micro time scales of the interphase diffusional mass transfer
process. As a result of this, the general PBE has no well known analytical solution and therefore robust
numerical solution methods with low computational cost are highly admired.
In this work, the Sectional Quadrature Method of Moments (SQMOM) (Attarakih, M. M., Drumm, C.,
Bart, H.-J. (2009). Solution of the population balance equation using the Sectional Quadrature Method of
Moments (SQMOM). Chem. Eng. Sci. 64, 742-752) is extended to take into account the continuous flow
systems in spatial domain. In this regard, the SQMOM is extended to solve the spatially distributed
nonhomogeneous bivariate PBE to model the hydrodynamics and physical/reactive mass transfer
behavior of liquid-liquid extraction equipment. Based on the extended SQMOM, two different steady
state and dynamic simulation algorithms for hydrodynamics and mass transfer behavior of liquid-liquid
extraction equipment are developed and efficiently implemented. At the steady state modeling level, a
Spatially-Mixed SQMOM (SM-SQMOM) algorithm is developed and successfully implemented in a onedimensional
physical spatial domain. The integral spatial numerical flux is closed using the mean mass
droplet diameter based on the One Primary and One Secondary Particle Method (OPOSPM which is the
simplest case of the SQMOM). On the other hand the hydrodynamics integral source terms are closed
using the analytical Two-Equal Weight Quadrature (TEqWQ). To avoid the numerical solution of the
droplet rise velocity, an analytical solution based on the algebraic velocity model is derived for the
particular case of unit velocity exponent appearing in the droplet swarm model. In addition to this, the
source term due to mass transport is closed using OPOSPM. The resulting system of ordinary differential
equations with respect to space is solved using the MATLAB adaptive Runge–Kutta method (ODE45). At
the dynamic modeling level, the SQMOM is extended to a one-dimensional physical spatial domain and
resolved using the finite volume method. To close the mathematical model, the required quadrature nodes
and weights are calculated using the analytical solution based on the Two Unequal Weights Quadrature
(TUEWQ) formula. By applying the finite volume method to the spatial domain, a semi-discreet ordinary
differential equation system is obtained and solved. Both steady state and dynamic algorithms are
extensively validated at analytical, numerical, and experimental levels. At the numerical level, the
predictions of both algorithms are validated using the extended fixed pivot technique as implemented in
PPBLab software (Attarakih, M., Alzyod, S., Abu-Khader, M., Bart, H.-J. (2012). PPBLAB: A new
multivariate population balance environment for particulate system modeling and simulation. Procedia
Eng. 42, pp. 144-562). At the experimental validation level, the extended SQMOM is successfully used
to model the steady state hydrodynamics and physical and reactive mass transfer behavior of agitated
liquid-liquid extraction columns under different operating conditions. In this regard, both models are
found efficient and able to follow liquid extraction column behavior during column scale-up, where three
column diameters were investigated (DN32, DN80, and DN150). To shed more light on the local
interactions among the contacted phases, a reduced coupled PBE and CFD framework is used to model
the hydrodynamic behavior of pulsed sieve plate columns. In this regard, OPOSPM is utilized and
implemented in FLUENT 18.2 commercial software as a special case of the SQMOM. The dropletdroplet
interactions
(breakage
and
coalescence)
are
taken
into
account
using
OPOSPM,
while
the
required
information
about
the
velocity
field
and
energy
dissipation
is
calculated
by
the
CFD
model.
In
addition
to
this,
the proposed coupled OPOSPM-CFD framework is extended to include the mass transfer. The
proposed framework is numerically tested and the results are compared with the published experimental
data. The required breakage and coalescence parameters to perform the 2D-CFD simulation are estimated
using PPBLab software, where a 1D-CFD simulation using a multi-sectional gird is performed. A very
good agreement is obtained at the experimental and the numerical validation levels.

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 \(\tilde{h}=1\).

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.

Analyzing Centrality Indices in Complex Networks: an Approach Using Fuzzy Aggregation Operators
(2018)

The identification of entities that play an important role in a system is one of the fundamental analyses being performed in network studies. This topic is mainly related to centrality indices, which quantify node centrality with respect to several properties in the represented network. The nodes identified in such an analysis are called central nodes. Although centrality indices are very useful for these analyses, there exist several challenges regarding which one fits best
for a network. In addition, if the usage of only one index for determining central
nodes leads to under- or overestimation of the importance of nodes and is
insufficient for finding important nodes, then the question is how multiple indices
can be used in conjunction in such an evaluation. Thus, in this thesis an approach is proposed that includes multiple indices of nodes, each indicating
an aspect of importance, in the respective evaluation and where all the aspects of a node’s centrality are analyzed in an explorative manner. To achieve this
aim, the proposed idea uses fuzzy operators, including a parameter for generating different types of aggregations over multiple indices. In addition, several preprocessing methods for normalization of those values are proposed and discussed. We investigate whether the choice of different decisions regarding the
aggregation of the values changes the ranking of the nodes or not. It is revealed that (1) there are nodes that remain stable among the top-ranking nodes, which
makes them the most central nodes, and there are nodes that remain stable
among the bottom-ranking nodes, which makes them the least central nodes; and (2) there are nodes that show high sensitivity to the choice of normalization
methods and/or aggregations. We explain both cases and the reasons why the nodes’ rankings are stable or sensitive to the corresponding choices in various networks, such as social networks, communication networks, and air transportation networks.

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.

The simulation of cutting process challenges established methods due to large deformations and topological changes. In this work a particle finite element method (PFEM) is presented, which combines the benefits of discrete modeling techniques and methods based on continuum mechanics. A crucial part of the PFEM is the detection of the boundary of a set of particles. The impact of this boundary detection method on the structural integrity is examined and a relation of the key parameter of the method to the eigenvalues of strain tensors is elaborated. The influence of important process parameters on the cutting force is studied and a comparison to an empirical relation is presented.