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The aim of this dissertation is to explain processes in recruitment by gaining a better understanding of how perceptions evolve and how recruitment outcomes and perceptions are influenced. To do so, this dissertation takes a closer look at the formation of fit perceptions, the effects of top employer awards on pre-hire recruitment outcomes, and on how perceptions about external sources are influenced.

In this work a 3-dimensional contact elasticity problem for a thin fiber and a rigid foundation is studied. We describe the contact condition by a linear Robin-condition (by meaning of the penalized and linearized non-penetration and friction conditions).
The dimension of the problem is reduced by an asymptotic approach. Scaling the Robin parameters appropriately we obtain a recurrent chain of Neumann type boundary value problems which are considered only in the microscopic scale. The problem for the leading term is a homogeneous Neumann problem, hence the leading term depends only on the slow variable. This motivates the choice of a multiplicative ansatz in the asymptotic expansion.
The theoretical results are illustrated with numerical examples performed with a commercial finite-element software-tool.

The Lagrangian field-antifield formalism of Batalin and Vilkovisky (BV) is used to investigate the application of the collec- tive coordinate method to soliton quantisation. In field theories with soliton solutions, the Gaussian fluctuation operator has zero modes due to the breakdown of global symmetries of the Lagrangian in the soliton solutions. It is shown how Noether identities and local symmetries of the Lagrangian arise when collective coordinates are introduced in order to avoid divergences related to these zero modes. This transformation to collective and fluctuation degrees of freedom is interpreted as a canonical transformation in the symplectic field-antifield space which induces a time-local gauge symmetry. Separating the corresponding Lagrangian path integral of the BV scheme in lowest order into harmonic quantum fluctuations and a free motion of the collective coordinate with the classical mass of the soliton, we show how the BV approach clarifies the relation between zero modes, collective coordinates, gauge invariance and the center- of-mass motion of classical solutions in quantum fields. Finally, we apply the procedure to the reduced nonlinear O(3) oe-model.^L

Based on experiences from an autonomous mobile robot project called MOBOT -III, we found hard realtime-constraints for the operating-system-design. ALBATROSS is "A flexible multi-tasking and realtime network-operatingsystem-kernel", not limited to mobile- robot-projects only, but which might be useful also wherever you have to guarantee a high reliability of a realtime-system. The focus in this article is on a communication-scheme fulfilling the demanded (hard realtime-) assurances although not implying time-delays or jitters on the critical informationchannels. The central chapters discuss a locking-free shared buffer management, without the need for interrupts and a way to arrange the communication architecture in order to produce minimal protocol-overhead and short cycle-times. Most of the remaining communication-capacity (if there is any) is used for redundant transfers, increasing the reliability of the whole system. ALBATROSS is actually implemented on a multi-processor VMEbus-system.

This paper refers to the problem of adaptability over an infinite period of time, regarding dynamic networks. A never ending flow of examples have to be clustered, based on a distance measure. The developed model is based on the self-organizing feature maps of Kohonen [6], [7] and some adaptations by Fritzke [3]. The problem of dynamic surface classification is embedded in the SPIN project, where sub-symbolic abstractions, based on a 3-d scanned environment is being done.

The problem to be discussed here, is the usage of neural network clustering techniques on a mobile robot, in order to build qualitative topologic environment maps. This has to be done in realtime, i.e. the internal world model has to be adapted by the flow of sensor- samples without the possibility to stop this data-flow.Our experiments are done in a simulation environment as well as on a robot, called ALICE.

Based on the experiences from an autonomous mobile robot project called MOBOT-III, we found hard realtime-constraints for the operating- system-design. ALBATROSS is "A flexible multi-tasking and realtime network-operating-system-kernel". The focusin this article is on a communication-scheme fulfilling the previous demanded assurances. The centralchapters discuss the shared buffer management and the way to design the communication architecture.Some further aspects beside the strict realtime-requirements like the possibilities to control and watch a running system, are mentioned. ALBATROSS is actually implemented on a multi-processor VMEbus-system.

Based on the idea of using topologic feature-mapsinstead of geometric environment maps in practical mobile robot tasks, we show an applicable way tonavigate on such topologic maps. The main features regarding this kind of navigation are: handling of very inaccurate position (and orientation) information as well as implicit modelling of complex kinematics during an adaptation phase. Due to the lack of proper a-priori knowledge, a re-inforcement based model is used for the translation of navigator commands to motor actions. Instead of employing a backpropagation network for the cen-tral associative memory module (attaching actionprobabilities to sensor situations resp. navigatorcommands) a much faster dynamic cell structure system based on dynamic feature maps is shown. Standard graph-search heuristics like A* are applied in the planning phase.

SPIN-NFDS Learning and Preset Knowledge for Surface Fusion - A Neural Fuzzy Decision System -
(1993)

The problem to be discussed in this paper may be characterized in short by the question: "Are these two surface fragments belonging together (i.e. belonging to the same surface)?" The presented techniques try to benefit from some predefined knowledge as well as from the possibility to refine and adapt this knowledge according to a (changing) real environment, resulting in a combination of fuzzy-decision systems and neural networks. The results are encouraging (fast convergence speed, high accuracy), and the model might be used for a wide range of applications. The general frame surrounding the work in this paper is the SPIN- project, where emphasis is on sub-symbolic abstractions, based on a 3-d scanned environment.

World models for mobile robots as introduced in many projects, are mostly redundant regarding similar situations detected in different places. The present paper proposes a method for dynamic generation of a minimal world model based on these redundancies. The technique is an extention of the qualitative topologic world modelling methods. As a central aspect the reliability regarding errortolerance and stability will be emphasized. The proposed technique demands very low constraints on the kind and quality of the employed sensors as well as for the kinematic precision of the utilized mobile platform. Hard realtime constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot "

This article will discuss a qualitative, topological and robust world-modelling technique with special regard to navigation-tasks for mobile robots operating in unknownenvironments. As a central aspect, the reliability regarding error-tolerance and stability will be emphasized. Benefits and problems involved in exploration, as well as in navigation tasks, are discussed. The proposed method demands very low constraints for the kind and quality of the employed sensors as well as for the kinematic precision of the utilized mobile platform. Hard real-time constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot

Self-localization in unknown environments respectively correlation of current and former impressions of the world is an essential ability for most mobile robots. The method,proposed in this article is the construction of a qualitative, topological world model as a basis for self-localization. As a central aspect the reliability regarding error-tolerance and stability will be emphasized. The proposed techniques demand very low constraints for the kind and quality of the employed sensors as well as for the kinematic precisionof the utilized mobile platform. Hard real-time constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot.

Visual Search has been investigated by many researchers inspired by the biological fact, that the sensory elements on the mammal retina are not equably distributed. Therefore the focus of attention (the area of the retina with the highest density of sensory elements) has to be directed in a way to efficiently gather data according to certain criteria. The work discussed in this article concentrates on applying a laser range finder instead of a silicon retina. The laser range finder is maximal focused at any time, but therefore a low resolution total-scene-image, available with camera-like devices from scratch on, cannot be used here. By adapting a couple of algorithms, the edge-scanning module steering the laser range finder is able to trace a detected edge. Based on the data scanned so far , two questions have to be answered. First: "Should the actual (edge-) scanning be interrupted in order to give another area of interest a chance of being investigated?" and second: "Where to start a new edge-scanning, after being interrupted?". These two decision-problems might be solved by a range of decision systems. The correctness of the decisions depends widely on the actual environment and the underlying rules may not be well initialized with a-priori knowledge. So we will present a version of a reinforcement decision system together with an overall scheme for efficiently controlling highly focused devices.

ALICE
(1994)

Matter-wave Optics of Dark-state Polaritons: Applications to Interferometry and Quantum Information
(2006)

The present work "Materwave Optics with Dark-state Polaritons: Applications to Interferometry and Quantum Information" deals in a broad sense with the subject of dark-states and in particular with the so-called dark-state polaritons introduced by M. Fleischhauer and M. D. Lukin. The dark-state polaritons can be regarded as a combined excitation of electromagnetic fields and spin/matter-waves. Within the framework of this thesis the special optical properties of the combined excitation are studied. On one hand a new procedure to spatially manipulate and to increase the excitation density of stored photons is described and on the other hand the properties are used to construct a new type of Sagnac Hybrid interferometer. The thesis is devided into four parts. In the introduction all notions necessary to understand the work are described, e.g.: electromagnetically induced transparency (EIT), dark-state polaritons and the Sagnac effect. The second chapter considers the method developed by A. Andre and M. D. Lukin to create stationary light pulses in specially dressed EIT-media. In a first step a set of field equations is derived and simplified by introducing a new set of normal modes. The absorption of one of the normal modes leads to the phenomenon of pulse-matching for the other mode and thereby to a diffusive spreading of its field envelope. All these considerations are based on a homogeneous field setup of the EIT preparation laser. If this restriction is dismissed one finds that a drift motion is superimposed to the diffusive spreading. By choosing a special laser configuration the drift motion can be tailored such that an effective force is created that counteracts the spreading. Moreover, the force can not only be strong enough to compensate the diffusive spreading but also to exceed this dynamics and hence to compress the field envelope of the excitation. The compression can be discribed using a Fokker-Planck equation of the Ornstein-Uhlenbeck type. The investigations show that the compression leads to an excitation of higher-order modes which decay very fast. In the last section of the chapter this exciation will be discussed in more detail and conditions will be given how the excitation of higher-order modes can be avoided or even suppressed. All results given in the chapter are supported by numerical simulatons. In the third chapter the matterwave optical properties of the dark-state polaritons will be studied. They will be used to construct a light-matterwave hybrid Sagnac interferometer. First the principle setup of such an interferometer will be sketched and the relevant equations of motion of light-matter interaction in a rotating frame will be derived. These form the basis of the following considerations of the dark-state polariton dynamics with and without the influence of external trapping potentials on the matterwave part of the polariton. It will be shown that a sensitivity enhancement compared to a passive laser gyroscope can be anticipated if the gaseous medium is initially in a superfluid quantum state in a ring-trap configuration. To achieve this enhancement a simultaneous coherence and momentum transfer is furthermore necessary. In the last part of the chapter the quantum sensitivity limit of the hybrid interferometer is derived using the one-particle density matrix equations incorporating the motion of the particles. To this end the Maxwell-Bloch equations are considered perturbatively in the rotation rate of the noninertial frame of reference and the susceptibility of the considered 3-level \(\Lambda\)-type system is derived in arbitrary order of the probe-field. This is done to determine the optimum operation point. With its help the anticipated quantum sensitivity of the light-matterwave hybrid Sagnac interferometer is calculated at the shot-noise limit and the results are compared to state-of-the-art laser and matterwave Sagnac interferometers. The last chapter of the thesis originates from a joint theoretical and experimental project with the AG Bergmann. This chapter does no longer consider the dark-state polaritons of the last two chapters but deals with the more general concept of dark states and in particular with the transient velocity selective dark states as introduced by E. Arimondo et al. In the experiment we could for the first time measure these states. The chapter starts with an introduction into the concept of velocity selective dark states as they occur in a \(\Lambda\)-configuration. Then we introduce the transient velocity selective dark-states as they occur in an particular extension of the \(\Lambda\)-system. For later use in the simulations the relevant equations of motion are derived in detail. The simulations are based on the solution of the generalized optical Bloch equations. Finally the experimental setup and procedure are explained and the theoretical and experimental results are compared.

To continue reducing voltage in scaled technologies, both circuit and architecture-level resiliency techniques are needed to tolerate process-induced defects, variation, and aging in SRAM cells. Many different resiliency schemes have been proposed and evaluated, but most prior results focus on voltage reduction instead of energy reduction. At the circuit level, device cell architectures and assist techniques have been shown to lower Vmin for SRAM, while at the architecture level, redundancy and cache disable techniques have been used to improve resiliency at low voltages. This paper presents a unified study of error tolerance for both circuit and architecture techniques and estimates their area and energy overheads. Optimal techniques are selected by evaluating both the error-correcting abilities at low supplies and the overheads of each technique in a 28nm. The results can be applied to many of the emerging memory technologies.

Abstract: We calculate exact analytical expressions for O(alpha s) 3-jet and O (alpha^2 s ) 4-jet cross sections in polarized deep inelastic lepton nucleon scattering. Introducing an invariant jet definition scheme, we present differential distributions of 3- and 4-jet cross sections in the basic kinematical variables x and W^2 as well as total jet cross sections and show their dependence on the chosen spin-dependent (polarized) parton distributions. Noticebly differences in the predictions are found for the two extreme choices, i.e. a large negative sea-quark density or a large positive gluon density. Therefore, it may be possible to discriminate between different parametrizations of polarized parton densities, and hence between the different physical pictures of the proton spin underlying these parametrizations.

A series of (oligo)phenthiazines, thiazolium salts and sulfonic acid functionalized organic/inorganic hybrid materials were synthesized. The organic groups were covalently bound on the inorganic surface through reactions of organosilane precursors with TEOS or with the silanol groups of material surface. These synthetic methods are called the co-condensation process and the post grafting. The structures and the textural parameters of the generated hybrid materials were characterized by XRD, N2 adsorption-desorption measurements, SEM and TEM. The incorporations of the organic groups were verified by elemental analysis, thermogravimetric analysis, FT-IR, UV-Vis, EPR, CV, as well as by 13C CP-MAS NMR and 29Si CP-MAS NMR spectroscopy. Introduction of various organic groups endow different phsysical, chemical properties to these hybrid materials. The (oligo)phenothiazines provide a group of novel redox acitive hybrid materials with special electronic and optic properties. The thiazolium salts modified materials were applied as heterogenized organo catalysts for the benzoin condensation and the cross-coupling of aldehydes with acylimines to yield a-amido ketones. The sulfonic acid containing materials can not only be used as Broensted acid catalysts, but also can serve as ion exchangable supports for further modifications and applications.

Nanoparticle-Filled Thermoplastics and Thermoplastic Elastomer: Structure-Property Relationships
(2012)

The present work focuses on the structure-property relationships of
particulate-filled thermoplastics and thermoplastic elastomer (TPE). In this work
two thermoplastics and one TPE were used as polymer matrices, i.e. amorphous
bisphenol-A polycarbonate (PC), semi-crystalline isotactic polypropylene (iPP),
and a block copolymer poly(butylene terephthalate)-block-poly(tetramethylene
glycol) TPE(PBT-PTMG). For PC, a selected type of various Aerosil® nano-SiO2
types was used as filler to improve the thermal and mechanical properties by
maintaining the transparency of PC matrix. Different types of SiO2 and TiO2
nanoparticles with different surface polarity were used for iPP. The goal was to
examine the influence of surface polarity and chemical nature of nanoparticles on
the thermal, mechanical and morphological properties of iPP composites. For
TPE(PBT-PTMG), three TiO2 particles were used, i.e. one grade with hydroxyl
groups on the particle surface and the other two grades are surface-modified with
metal and metal oxides, respectively. The influence of primary size and dispersion
quality of TiO2 particles on the properties of TPE(PBT-PTMG)/TiO2 composites
were determined and discussed.
All polymer composites were produced by direct melt blending in a twin-screw
extruder via masterbatch technique. The dispersion of particles was examined by
using scanning electron microscopy (SEM) and micro-computerized tomography
(μCT). The thermal and crystalline properties of polymer composites were characterized by using thermogravimetric analysis (TGA) and differential
scanning calorimetry (DSC). The mechanical and thermomechanical properties
were determined by using mechanical tensile testing, compact tension and
Charpy impact as well as dynamic-mechanical thermal analysis (DMTA).
The SEM results show that the unpolar-surface modified nanoparticles are better
dispersed in polymer matrices as iPP than polar-surface nanoparticles, especially
in case of using Aeroxide® TiO2 nanoparticles. The Aeroxide® TiO2 nanoparticles
with a polar surface due to Ti-OH groups result in a very high degree of
agglomeration in both iPP and TPE matrices because of strong van der Waals
interactions among particles (hydrogen bonding). Compared to unmodified
Aeroxide® TiO2 nanoparticles, the other grades of surface modified TiO2 particles
are very homogenously dispersed in used iPP and TPE(PBT-PTMG). The
incorporation of SiO2 nanoparticles into bisphenol-A PC significantly increases
the mechanical properties of PC/SiO2 nanocomposites, particularly the resistance
against environmental stress crazing (ESC). However, the transparency of
PC/SiO2 nanocomposites decreases with increasing nanoparticle content and
size due to a mismatch of infractive indices of PC and SiO2 particles. The different
surface polarity of nanoparticles in iPP shows evident influence on properties of
iPP composites. Among iPP/SiO2 nanocomposites, the nanocomposite
containing SiO2 nanoparticles with a higher degree of hydrophobicity shows
improved fracture and impact toughness compared to the other iPP/SiO2
composites. The TPE(PBT-PTMG)/TiO2 composites show much better thermal and mechanical properties than neat TPE(PBT-PTMG) due to strong chemical
interactions between polymer matrix and TiO2 particles. In addition, better
dispersion quality of TiO2 particles in used TPE(PBT-PTMG) leads to dramatically
improved mechanical properties of TPE(PBT-PTMG)/TiO2 composites.

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

We propose and study a strongly coupled PDE-ODE system with tissue-dependent degenerate diffusion and haptotaxis that can serve as a model prototype for cancer cell invasion through the
extracellular matrix. We prove the global existence of weak solutions and illustrate the model behaviour by numerical simulations for a two-dimensional setting.

We propose and study a strongly coupled PDE-ODE-ODE system modeling cancer cell invasion through a tissue network
under the go-or-grow hypothesis asserting that cancer cells can either move or proliferate. Hence our setting features
two interacting cell populations with their mutual transitions and involves tissue-dependent degenerate diffusion and
haptotaxis for the moving subpopulation. The proliferating cells and the tissue evolution are characterized by way of ODEs
for the respective densities. We prove the global existence of weak solutions and illustrate the model behaviour by
numerical simulations in a two-dimensional setting.

Whole-body vibrations (WBV) have adverse effects on ride comfort and human health. Suspension seats have an important influence on the WBV severity. In this study, WBV were measured on a medium-sized compact wheel loader (CWL) in its typical operations. The effect of short-term exposure to the WBV on the ride comfort was evaluated according to ISO 2631-1:1985 and ISO 2631-1:1997. ISO 2631-1:1997 and ISO 2631-5:2004 were adopted to evaluate the effect of long-term exposure to the WBV on the human health. Reasons for the different evaluation results obtained according to ISO 2631-1:1997 and ISO 2631-5:2004 were explained in this study. The WBV measurements were carried out in cases where the driver wore a lap belt or a four-point seat harness and in the case where the driver did not wear any safety belt. The seat effective amplitude transmissibility (SEAT) and the seat transmissibility in the frequency domain in these three cases were analyzed to investigate the effect of a safety belt on the seat transmissibility. Seat tests were performed on a multi-axis shaking table in laboratory to study the dynamic behavior of a suspension seat under the vibration excitations measured on the CWL. The WBV intensity was reduced by optimizing the vertical and the longitudinal seat suspension systems with the help of computational simulations. For the optimization multi-body models of the seat-dummy system in the laboratory seat tests and the seat-driver system in the field vibration measurements were built and validated.

A new method is used to investigate the tunneling between two weakly-linked Bose-Einstein con- densates confined in double-well potential traps. The nonlinear interaction between the atoms in each well contributes to a finite chemical potential, which, with consideration of periodic instantons, leads to a remarkably high tunneling frequency. This result can be used to interpret the newly found Macroscopic Quantum Self Trapping (MQST) effect. Also a new kind of first-order crossover between different regions is predicted.

The main purpose of the study was to improve the physical properties of the modelling of compressed materials, especially fibrous materials. Fibrous materials are finding increasing application in the industries. And most of the materials are compressed for different applications. For such situation, we are interested in how the fibre arranged, e.g. with which distribution. For given materials it is possible to obtain a three-dimensional image via micro computed tomography. Since some physical parameters, e.g. the fibre lengths or the directions for points in the fibre, can be checked under some other methods from image, it is beneficial to improve the physical properties by changing the parameters in the image.
In this thesis, we present a new maximum-likelihood approach for the estimation of parameters of a parametric distribution on the unit sphere, which is various as some well known distributions, e.g. the von-Mises Fisher distribution or the Watson distribution, and for some models better fit. The consistency and asymptotic normality of the maximum-likelihood estimator are proven. As the second main part of this thesis, a general model of mixtures of these distributions on a hypersphere is discussed. We derive numerical approximations of the parameters in an Expectation Maximization setting. Furthermore we introduce a non-parametric estimation of the EM algorithm for the mixture model. Finally, we present some applications to the statistical analysis of fibre composites.

In recent years, nanofiller-reinforced polymer composites have attracted considerable
interest from numerous researchers, since they can offer unique mechanical,
electrical, optical and thermal properties compared to the conventional polymer
composites filled with micron-sized particles or short fibers. With this background, the
main objective of the present work was to investigate the various mechanical
properties of polymer matrices filled with different inorganic rigid nanofillers, including
SiOB2B, TiOB2B, AlB2BOB3B and multi-walled carbon nanotubes (MWNT). Further, special
attention was paid to the fracture behaviours of the polymer nanocomposites. The
polymer matrices used in this work contained two types of epoxy resin (cycloaliphatic
and bisphenol-F) and two types of thermoplastic polymer (polyamide 66 and isotactic
polypropylene).
The epoxy-based nanocomposites (filled with nano-SiOB2B) were formed in situ by a
special sol-gel technique supplied by nanoresins AG. Excellent nanoparticle
dispersion was achieved even at rather high particle loading. The almost
homogeneously distributed nanoparticles can improve the elastic modulus and
fracture toughness (characterized by KBICB and GBICB) simultaneously. According to
dynamic mechanical and thermal analysis (DMTA), the nanosilica particles in epoxy
resins possessed considerable "effective volume fraction" in comparison with their
actual volume fraction, due to the presence of the interphase. Moreover, AFM and
high-resolution SEM observations also suggested that the nanosilica particles were
coated with a polymer layer and therefore a core-shell structure of particle-matrix was
expected. Furthermore, based on SEM fractography, several toughening
mechanisms were considered to be responsible for the improvement in toughness,
which included crack deflection, crack pinning/bowing and plastic deformation of
matrix induced by nanoparticles.
The PA66 or iPP-based nanocomposites were fabricated by a conventional meltextrusion
technique. Here, the nanofiller content was set constant as 1 vol.%. Relatively good particle dispersion was found, though some small aggregates still
existed. The elastic modulus of both PA66 and iPP was moderately improved after
incorporation of the nanofillers. The fracture behaviours of these materials were
characterized by an essential work fracture (EWF) approach. In the case of PA66
system, the EWF experiments were carried out over a broad temperature range
(23~120 °C). It was found that the EWF parameters exhibited high temperature
dependence. At most testing temperatures, a small amount of nanoparticles could
produce obvious toughening effects at the cost of reduction in plastic deformation of
the matrix. In light of SEM fractographs and crack opening tip (COD) analysis, the
crack blunting induced by nanoparticles might be the major source of this toughening.
The fracture behaviours of PP filled with MWNTs were investigated over a broad
temperature range (-196~80 °C) in terms of notched impact resistance. It was found
that MWNTs could enhance the notched impact resistance of PP matrix significantly
once the testing temperature was higher than the glass transition temperature (TBgB) of
neat PP. At the relevant temperature range, the longer the MWNTs, the better was
the impact resistance. SEM observation revealed three failure modes of nanotubes:
nanotube bridging, debonding/pullout and fracture. All of them would contribute to
impact toughness to a degree. Moreover, the nanotube fracture was considered as
the major failure mode. In addition, the smaller spherulites induced by the nanotubes
would also benefit toughness.

Nowadays, accounting, charging and billing users' network resource consumption are commonly used for the purpose of facilitating reasonable network usage, controlling congestion, allocating cost, gaining revenue, etc. In traditional IP traffic accounting systems, IP addresses are used to identify the corresponding consumers of the network resources. However, there are some situations in which IP addresses cannot be used to identify users uniquely, for example, in multi-user systems. In these cases, network resource consumption can only be ascribed to the owners of these hosts instead of corresponding real users who have consumed the network resources. Therefore, accurate accountability in these systems is practically impossible. This is a flaw of the traditional IP address based IP traffic accounting technique. This dissertation proposes a user based IP traffic accounting model which can facilitate collecting network resource usage information on the basis of users. With user based IP traffic accounting, IP traffic can be distinguished not only by IP addresses but also by users. In this dissertation, three different schemes, which can achieve the user based IP traffic accounting mechanism, are discussed in detail. The inband scheme utilizes the IP header to convey the user information of the corresponding IP packet. The Accounting Agent residing in the measured host intercepts IP packets passing through it. Then it identifies the users of these IP packets and inserts user information into the IP packets. With this mechanism, a meter located in a key position of the network can intercept the IP packets tagged with user information, extract not only statistic information, but also IP addresses and user information from the IP packets to generate accounting records with user information. The out-of-band scheme is a contrast scheme to the in-band scheme. It also uses an Accounting Agent to intercept IP packets and identify the users of IP traffic. However, the user information is transferred through a separated channel, which is different from the corresponding IP packets' transmission. The Multi-IP scheme provides a different solution for identifying users of IP traffic. It assigns each user in a measured host a unique IP address. Through that, an IP address can be used to identify a user uniquely without ambiguity. This way, traditional IP address based accounting techniques can be applied to achieve the goal of user based IP traffic accounting. In this dissertation, a user based IP traffic accounting prototype system developed according to the out-of-band scheme is also introduced. The application of user based IP traffic accounting model in the distributed computing environment is also discussed.

Conditional Compilation (CC) is frequently used as a variation mechanism in software product lines (SPLs). However, as a SPL evolves the variable code realized by CC erodes in the sense that it becomes overly complex and difficult to understand and maintain. As a result, the SPL productivity goes down and puts expected advantages more and more at risk. To investigate the variability erosion and keep the productivity above a sufficiently good level, in this paper we 1) investigate several erosion symptoms in an industrial SPL; 2) present a variability improvement process that includes two major improvement strategies. While one strategy is to optimize variable code within the scope of CC, the other strategy is to transition CC to a new variation mechanism called Parameterized Inclusion. Both of these two improvement strategies can be conducted automatically, and the result of CC optimization is provided. Related issues such as applicability and cost of the improvement are also discussed.

As a Software Product Line (SPL) evolves with increasing number of features and feature values, the feature correlations become extremely intricate, and the specifications of these correlations tend to be either incomplete or inconsistent with their realizations, causing misconfigurations in practice. In order to guide product configuration processes, we present a solution framework to recover complex feature correlations from existing product configurations. These correlations are further pruned automatically and validated by domain experts. During implementation, we use association mining techniques to automatically extract strong association rules as potential feature correlations. This approach is evaluated using a large-scale industrial SPL in the embedded system domain, and finally we identify a large number of complex feature correlations.

This thesis is devoted to deal with the stochastic optimization problems in various situations with the aid of the Martingale method. Chapter 2 discusses the Martingale method and its applications to the basic optimization problems, which are well addressed in the literature (for example, [15], [23] and [24]). In Chapter 3, we study the problem of maximizing expected utility of real terminal wealth in the presence of an index bond. Chapter 4, which is a modification of the original research paper joint with Korn and Ewald [39], investigates an optimization problem faced by a DC pension fund manager under inflationary risk. Although the problem is addressed in the context of a pension fund, it presents a way of how to deal with the optimization problem, in the case there is a (positive) endowment. In Chapter 5, we turn to a situation where the additional income, other than the income from returns on investment, is gained by supplying labor. Chapter 6 concerns a situation where the market considered is incomplete. A trick of completing an incomplete market is presented there. The general theory which supports the discussion followed is summarized in the first chapter.

In this work, we analyze two important and simple models of short rates, namely Vasicek and CIR models. The models are described and then the sensitivity of the models with respect to changes in the parameters are studied. Finally, we give the results for the estimation of the model parameters by using two different ways.

Automata theory has given rise to a variety of automata models that consist
of a finite-state control and an infinite-state storage mechanism. The aim
of this work is to provide insights into how the structure of the storage
mechanism influences the expressiveness and the analyzability of the
resulting model. To this end, it presents generalizations of results about
individual storage mechanisms to larger classes. These generalizations
characterize those storage mechanisms for which the given result remains
true and for which it fails.
In order to speak of classes of storage mechanisms, we need an overarching
framework that accommodates each of the concrete storage mechanisms we wish
to address. Such a framework is provided by the model of valence automata,
in which the storage mechanism is represented by a monoid. Since the monoid
serves as a parameter to specifying the storage mechanism, our aim
translates into the question: For which monoids does the given
(automata-theoretic) result hold?
As a first result, we present an algebraic characterization of those monoids
over which valence automata accept only regular languages. In addition, it
turns out that for each monoid, this is the case if and only if valence
grammars, an analogous grammar model, can generate only context-free
languages.
Furthermore, we are concerned with closure properties: We study which
monoids result in a Boolean closed language class. For every language class
that is closed under rational transductions (in particular, those induced by
valence automata), we show: If the class is Boolean closed and contains any
non-regular language, then it already includes the whole arithmetical
hierarchy.
This work also introduces the class of graph monoids, which are defined by
finite graphs. By choosing appropriate graphs, one can realize a number of
prominent storage mechanisms, but also combinations and variants thereof.
Examples are pushdowns, counters, and Turing tapes. We can therefore relate
the structure of the graphs to computational properties of the resulting
storage mechanisms.
In the case of graph monoids, we study (i) the decidability of the emptiness
problem, (ii) which storage mechanisms guarantee semilinear Parikh images,
(iii) when silent transitions (i.e. those that read no input) can be
avoided, and (iv) which storage mechanisms permit the computation of
downward closures.

Algebraic Systems Theory
(2004)

Control systems are usually described by differential equations, but their properties of interest are most naturally expressed in terms of the system trajectories, i.e., the set of all solutions to the equations. This is the central idea behind the so-called "behavioral approach" to systems and control theory. On the other hand, the manipulation of linear systems of differential equations can be formalized using algebra, more precisely, module theory and homological methods ("algebraic analysis"). The relationship between modules and systems is very rich, in fact, it is a categorical duality in many cases of practical interest. This leads to algebraic characterizations of structural systems properties such as autonomy, controllability, and observability. The aim of these lecture notes is to investigate this module-system correspondence. Particular emphasis is put on the application areas of one-dimensional rational systems (linear ODE with rational coefficients), and multi-dimensional constant systems (linear PDE with constant coefficients).

These lecture notes give a completely self-contained introduction to the control theory of linear time-invariant systems. No prior knowledge is requried apart from linear algebra and some basic familiarity with ordinary differential equations. Thus, the course is suited for students of mathematics in their second or third year, and for theoretically inclined engineering students. Because of its appealing simplicity and elegance, the behavioral approch has been adopted to a large extend. A short list of recommended text books on the subject has been added, as a suggestion for further reading.

In this paper mathematical models for liquid films generated by impinging jets are discussed. Attention is stressed to the interaction of the liquid film with some obstacle. S. G. Taylor [Proc. R. Soc. London Ser. A 253, 313 (1959)] found that the liquid film generated by impinging jets is very sensitive to properties of the wire which was used as an obstacle. The aim of this presentation is to propose a modification of the Taylor's model, which allows to simulate the film shape in cases, when the angle between jets is different from 180°. Numerical results obtained by discussed models give two different shapes of the liquid film similar as in Taylors experiments. These two shapes depend on the regime: either droplets are produced close to the obstacle or not. The difference between two regimes becomes larger if the angle between jets decreases. Existence of such two regimes can be very essential for some applications of impinging jets, if the generated liquid film can have a contact with obstacles.

Continuum Mechanical Modeling of Dry Granular Systems: From Dilute Flow to Solid-Like Behavior
(2014)

In this thesis, we develop a granular hydrodynamic model which covers the three principal regimes observed in granular systems, i.e. the dilute flow, the dense flow and the solid-like regime. We start from a kinetic model valid at low density and extend its validity to the granular solid-like behavior. Analytical and numerical results show that this model reproduces a lot of complex phenomena like for instance slow viscoplastic motion, critical states and the pressure dip in sand piles. Finally we formulate a 1D version of the full model and develop a numerical method to solve it. We present two numerical examples, a filling simulation and the flow on an inclined plane where the three regimes are included.

Granular systems in solid-like state exhibit properties like stiffness
dependence on stress, dilatancy, yield or incremental non-linearity
that can be described within the continuum mechanical framework.
Different constitutive models have been proposed in the literature either based on relations between some components of the stress tensor or on a quasi-elastic description. After a brief description of these
models, the hyperelastic law recently proposed by Jiang and Liu [1]
will be investigated. In this framework, the stress-strain relation is
derived from an elastic strain energy density where the stable proper-
ties are linked to a Drucker-Prager yield criteria. Further, a numerical method based on the finite element discretization and Newton-
Raphson iterations is presented to solve the force balance equation.
The 2D numerical examples presented in this work show that the stress
distributions can be computed not only for triangular domains, as previoulsy done in the literature, but also for more complex geometries.
If the slope of the heap is greater than a critical value, numerical instabilities appear and no elastic solution can be found, as predicted by
the theory. As main result, the dependence of the material parameter
Xi on the maximum angle of repose is established.

Wireless LANs operating within unlicensed frequency bands require random access schemes such as CSMA/ CA, so that wireless networks from different administrative domains (for example wireless community networks) may co-exist without central coordination, even when they happen to operate on the same radio channel. Yet, it is evident that this Jack of coordination leads to an inevitable loss in efficiency due to contention on the MAC layer. The interesting question is, which efficiency may be gained by adding coordination to existing, unrelated wireless networks, for example by self-organization. In this paper, we present a methodology based on a mathematical programming formulation to determine the
parameters (assignment of stations to access points, signal strengths and channel assignment of both access points and stations) for a scenario of co-existing CSMA/ CA-based wireless networks, such that the contention between these networks is minimized. We demonstrate how it is possible to solve this discrete, non-linear optimization problem exactly for small
problems. For larger scenarios, we present a genetic algorithm specifically tuned for finding near-optimal solutions, and compare its results to theoretical lower bounds. Overall, we provide a benchmark on the minimum contention problem for coordination mechanisms in CSMA/CA-based wireless networks.

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.

On the Extended Finite Element Method for the Elasto-Plastic Deformation of Heterogeneous Materials
(2015)

This thesis is concerned with the extended finite element method (XFEM) for deformation analysis of three-dimensional heterogeneous materials. Using the "enhanced abs enrichment" the XFEM is able to reproduce kinks in the displacements and therewith jumps in the strains within elements of the underlying tetrahedral finite element mesh. A complex model for the micro structure reconstruction of aluminum matrix composite AMC225xe and the modeling of its macroscopic thermo-mechanical plastic deformation behavior is presented, using the XFEM. Additionally, a novel stabilization algorithm is introduced for the XFEM. This algorithm requires preprocessing only.

Point-to-Point Trajectory Planning of Flexible Redundant Robot Manipulators Using Genetic Algorithms
(2001)

The paper focuses on the problem of point-to-point trajectory planning for flexible redundant robot manipulators (FRM) in joint space. Compared with irredundant flexible manipulators, a FRM possesses additional possibilities during point-to-point trajectory planning due to its kinematics redundancy. A trajectory planning method to minimize vibration and/or executing time of a point-to-point motion is presented for FRM based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as planning variables. Quadrinomial and quintic polynomial are used to describe the segments that connect the initial, intermediate, and final points in joint space. The trajectory planning of FRM is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. Case studies show that the method is applicable.

The paper focuses on the problem of trajectory planning of flexible redundant robot manipulators (FRM) in joint space. Compared to irredundant flexible manipulators, FRMs present additional possibilities in trajectory planning due to their kinematics redundancy. A trajectory planning method to minimize vibration of FRMs is presented based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as a planning variable. Quadrinomial and quintic polynomials are used to describe the segments which connect the initial, intermediate, and final points in joint space. The trajectory planning of FRMs is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. A case study shows that the method is applicable.

It is difficult for robots to handle a vibrating deformable object. Even for human beings it is a high-risk operation to, for example, insert a vibrating linear object into a small hole. However, fast manipulation using a robot arm is not just a dream; it may be achieved if some important features of the vibration are detected online. In this paper, we present an approach for fast manipulation using a force/torque sensor mounted on the robot's wrist. Template matching method is employed to recognize the vibrational phase of the deformable objects. Therefore, a fast manipulation can be performed with a high success rate, even if there is acute vibration. Experiments inserting a deformable object into a hole are conducted to test the presented method. Results demonstrate that the presented sensor-based online fast manipulation is feasible.

The vibration induced in a deformable object upon automatic handling by robot manipulators can often be bothersome. This paper presents a force/torque sensor-based method for handling deformable linear objects (DLOs) in a manner suitable to eliminate acute vibration. An adjustment-motion that can be attached to the end of an arbitrary end-effector's trajectory is employed to eliminate vibration of deformable objects. Differently from model-based methods, the presented sensor-based method does not employ any information from previous motions. The adjustment-motion is generated automatically by analyzing data from a force/torque sensor mounted on the robot wrist. Template matching technique is used to find out the matching point between the vibrational signal of the DLO and a template. Experiments are conducted to test the new method under various conditions. Results demonstrate the effectiveness of the sensor-based adjustment-motion.

Manipulating Deformable Linear Objects: Attachable Adjustment-Motions for Vibration Reduction
(2001)

This paper addresses the problem of handling deformable linear objects (DLOs) in a suitable way to avoid acute vibration. Different types of adjustment-motions that eliminate vibration of deformable objects and can be attached to the end of an arbitrary end-effector trajectory are presented. For describing the dynamics of deformable linear objects, the finite element method is used to derive the dynamic differential equations. Genetic algorithm is used to find the optimal adjustment motion for each simulation example. Experiments are conducted to verify the presented manipulating method.

Manipulating Deformable Linear Objects: Model-Based Adjustment-Motion for Vibration Reduction
(2001)

This paper addresses the problem of handling deformable linear objects (DLOs) in a suitable way to avoid acute vibration. An adjustment-motion that eliminates vibration of DLOs and can be attached to the end of any arbitrary end-effector's trajectory is presented, based on the concept of open-loop control. The presented adjustment-motion is a kind of agile end-effector motion with limited scope. To describe the dynamics of deformable linear objects, the finite element method is used to derive the dynamic differential equations. Genetic algorithm is used to find the optimal adjustment-motion for each simulation example. In contrast to previous approaches, the presented method can be treated as one of the manipulation skills and can be applied to different cases without major changes to the method.

Abstract: We present experimental and theoretical results of a detailed study of laser-induced continuum structures (LICS) in the photoionization continuum of helium out of the metastable state 2s^1 S_0. The continuum dressing with a 1064 nm laser, couples the same region of the continuum to the 4s^1 S_0 state. The experimental data, presented for a range of intensities, show pronounced ionization suppression (by asmuch as 70% with respect to the far-from-resonance value) as well as enhancement, in a Beutler-Fano resonance profile. This ionization suppression is a clear indication of population trapping mediated by coupling to a contiuum. We present experimental results demonstrating the effect of pulse delay upon the LICS, and for the behavior of LICS for both weak and strong probe pulses. Simulations based upon numerical solution of the Schrödinger equation model the experimental results. The atomic parameters (Rabi frequencies and Stark shifts) are calculated using a simple model-potential method for the computation of the needed wavefunctions. The simulations of the LICS profiles are in excellent agreement with experiment. We also present an analytic formulation of pulsed LICS. We show that in the case of a probe pulse shorter than the dressing one the LICS profile is the convolution of the power spectra of the probe pulse with the usual Fano profile of stationary LICS. We discuss some consequences of deviation from steady-state theory.

This work introduces a promising concept for the preparation of new nano-sized receptors. Mixed monolayer protected gold nanoparticles (AuNPs) for low molecular weight compounds were prepared featuring functional groups on their surfaces. It has been shown that these AuNPs can engage in interactions with peptides in aqueous media. Quantitative binding information was obtained from DOSY-NMR titrations indicating that nanoparticles containing a combination of three orthogonal functional groups are more efficient in binding to dipeptides than mono or difunctionalised analogues. The strategy is highly modular and easily allows adapting the receptor selectivity to a
given substrate by varying the type, number, and ratio of binding sites on the nanoparticle
surface.

The safety of embedded systems is becoming more and more important nowadays. Fault Tree Analysis (FTA) is a widely used technique for analyzing the safety of embedded systems. A standardized tree-like structure called a Fault Tree (FT) models the failures of the systems. The Component Fault Tree (CFT) provides an advanced modeling concept for adapting the traditional FTs to the hierarchical architecture model in system design. Minimal Cut Set (MCS) analysis is a method that works for qualitative analysis based on the FTs. Each MCS represents a minimal combination of component failures of a system called basic events, which may together cause the top-level system failure. The ordinary representations of MCSs consist of plain text and data tables with little additional supporting visual and interactive information. Importance analysis based on FTs or CFTs estimates the contribution of each potential basic event to a top-level system failure. The resulting importance values of basic events are typically represented in summary views, e.g., data tables and histograms. There is little visual integration between these forms and the FT (or CFT) structure. The safety of a system can be improved using an iterative process, called the safety improvement process, based on FTs taking relevant constraints into account, e.g., cost. Typically, relevant data regarding the safety improvement process are presented across multiple views with few interactive associations. In short, the ordinary representation concepts cannot effectively facilitate these analyses.
We propose a set of visualization approaches for addressing the issues above mentioned in order to facilitate those analyses in terms of the representations.
Contribution:
1. To support the MCS analysis, we propose a matrix-based visualization that allows detailed data of the MCSs of interest to be viewed while maintaining a satisfactory overview of a large number of MCSs for effective navigation and pattern analysis. Engineers can also intuitively analyze the influence of MCSs of a CFT.
2. To facilitate the importance analysis based on the CFT, we propose a hybrid visualization approach that combines the icicle-layout-style architectural views with the CFT structure. This approach facilitates to identify the vulnerable components taking the hierarchies of system architecture into account and investigate the logical failure propagation of the important basic events.
3. We propose a visual safety improvement process that integrates an enhanced decision tree with a scatter plot. This approach allows one to visually investigate the detailed data related to individual steps of the process while maintaining the overview of the process. The approach facilitates to construct and analyze improvement solutions of the safety of a system.
Using our visualization approaches, the MCS analysis, the importance analysis, and the safety improvement process based on the CFT can be facilitated.

The noise issue in manufacturing system is widely discussed from legal and health aspects. Regarding the existing laws and guidelines, various investigation methods are implemented in industry. The sound pressure level can be measured and reduced by using established approaches in reality. However, a straightforward and low cost approach to study noise issue using existing digital factory models is not found.
This thesis attempts to develop a novel concept for sound pressure level investigation in a virtual environment. With this, the factory planners are able to investigate the noise issue during factory design and layout planning phase.
Two computer aided tools are used in this approach: acoustic simulation and virtual reality (VR). The former enables the planner to simulate the sound pressure level by given factory layout and facility sound features. And the latter provides a visualization environment to view and explore the simulation results. The combination of these two powerful tools provides the planners a new possibility to analyze the noise in a factory.
To validate the simulations, the acoustic measurements are implemented in a real factory. Sound pressure level and sound intensity are determined respectively. Furthermore, a software tool is implemented using the introduced concept and approach. With this software, the simulation results are represented in a Cave Automatic Virtual Environment (CAVE).
This thesis describes the development of the approach, the measurement of sound features, the design of visualization framework, and the implementation of VR software. Based on this know-how, the industry users are able to design their own method and software for noise investigation and analysis.

The broad engineering applications of polymers and composites have become the
state of the art due to their numerous advantages over metals and alloys, such as
lightweight, easy processing and manufacturing, as well as acceptable mechanical
properties. However, a general deficiency of thermoplastics is their relatively poor
creep resistance, impairing service durability and safety, which is a significant barrier
to further their potential applications. In recent years, polymer nanocomposites have
been increasingly focused as a novel field in materials science. There are still many
scientific questions concerning these materials leading to the optimal property
combinations. The major task of the current work is to study the improved creep
resistance of thermoplastics filled with various nanoparticles and multi-walled carbon
nanotubes.
A systematic study of three different nanocomposite systems by means of
experimental observation and modeling and prediction was carried out. In the first
part, a nanoparticle/PA system was prepared to undergo creep tests under different
stress levels (20, 30, 40 MPa) at various temperatures (23, 50, 80 °C). The aim was
to understand the effect of different nanoparticles on creep performance. 1 vol. % of
300 nm and 21 nm TiO2 nanoparticles and nanoclay was considered. Surface
modified 21 nm TiO2 particles were also investigated. Static tensile tests were
conducted at those temperatures accordingly. It was found that creep resistance was
significantly enhanced to different degrees by the nanoparticles, without sacrificing
static tensile properties. Creep was characterized by isochronous stress-strain curves,
creep rate, and creep compliance under different temperatures and stress levels.
Orientational hardening, as well as thermally and stress activated processes were
briefly introduced to further understanding of the creep mechanisms of these
nanocomposites. The second material system was PP filled with 1 vol. % 300 nm and 21 nm TiO2
nanoparticles, which was used to obtain more information about the effect of particle
size on creep behavior based on another matrix material with much lower Tg. It was
found especially that small nanoparticles could significantly improve creep resistance.
Additionally, creep lifetime under high stress levels was noticeably extended by
smaller nanoparticles. The improvement in creep resistance was attributed to a very
dense network formed by the small particles that effectively restricted the mobility of
polymer chains. Changes in the spherulite morphology and crystallinity in specimens
before and after creep tests confirmed this explanation.
In the third material system, the objective was to explore the creep behavior of PP
reinforced with multi-walled carbon nanotubes. Short and long aspect ratio nanotubes
with 1 vol. % were used. It was found that nanotubes markedly improved the creep
resistance of the matrix, with reduced creep deformation and rate. In addition, the
creep lifetime of the composites was dramatically extended by 1,000 % at elevated
temperatures. This enhancement contributed to efficient load transfer between
carbon nanotubes and surrounding polymer chains.
Finally, a modeling analysis and prediction of long-term creep behaviors presented a
comprehensive understanding of creep in the materials studied here. Both the
Burgers model and Findley power law were applied to satisfactorily simulate the
experimental data. The parameter analysis based on Burgers model provided an
explanation of structure-to-property relationships. Due to their intrinsic difference, the
power law was more capable of predicting long-term behaviors than Burgers model.
The time-temperature-stress superposition principle was adopted to predict long-term
creep performance based on the short-term experimental data, to make it possible to
forecast the future performance of materials.

Radiotherapy is one of the major forms in cancer treatment. The patient is irradiated with high-energetic photons or charged particles with the primary goal of delivering sufficiently high doses to the tumor tissue while simultaneously sparing the surrounding healthy tissue. The inverse search for the treatment plan giving the desired dose distribution is done by means of numerical optimization [11, Chapters 3-5]. For this purpose, the aspects of dose quality in the tissue are modeled as criterion functions, whose mathematical properties also affect the type of the corresponding optimization problem. Clinical practice makes frequent use of criteria that incorporate volumetric and spatial information about the shape of the dose distribution. The resulting optimization problems are of global type by empirical knowledge and typically computed with generic global solver concepts, see for example [16]. The development of good global solvers to compute radiotherapy optimization problems is an important topic of research in this application, however, the structural properties of the underlying criterion functions are typically not taken into account in this context.

Elastomers and their various composites, and blends are frequently used as engineering working parts subjected to rolling friction movements. This fact already substantiates the importance of a study addressing the rolling tribological properties of elastomers and their compounds. It is worth noting that until now the research and development works on the friction and wear of rubber materials were mostly focused on abrasion and to lesser extent on sliding type of loading. As the tribological knowledge acquired with various counterparts, excluding rubbers, can hardly be adopted for those with rubbers, there is a substantial need to study the latter. Therefore, the present work was aimed at investigating the rolling friction and wear properties of different kinds of elastomers against steel under unlubricated condition. In the research the rolling friction and wear properties of various rubber materials were studied in home-made rolling ball-on-plate test configurations under dry condition. The materials inspected were ethylene/propylene/diene rubber (EPDM) without and with carbon black (EPDM_CB), hydrogenated acrylonitrile/butadiene rubber (HNBR) without and with carbon black/silica/multiwall carbon nanotube (HNBR_CB/silica/MWCNT), rubber-rubber hybrid (HNBR and fluororubber (HNBR-FKM)) and rubber-thermoplastic blend (HNBR and cyclic butylene terephthalate oligomers (HNBR-CBT)). The dominant wear mechanisms were investigated by scanning electron microscopy (SEM), and analyzed as a function of composition and testing conditions. Differential scanning calorimetry (DSC), dynamic-mechanical thermal analysis (DMTA), atomic force microscopy (AFM), and transmission electron microscopy (TEM) along with other auxiliary measurements, were adopted to determine the phase structure and network-related properties of the rubber systems. The changes of the friction and wear as a function of type and amount of the additives were explored. The friction process of selected rubbers was also modelled by making use of the finite element method (FEM). The results show that incorporation of filler enhanced generally the wear resistance, hardness, stiffness (storage modulus), and apparent crosslinking of the related rubbers (EPDM-, HNBR- and HNBR-FKM based ones), but did not affect their glass transition temperature. Filling of rubbers usually reduced the coefficient of friction (COF). However, the tribological parameters strongly depended also on the test set-up and test duration. High wear loss was noticed for systems showing the occurrence of Schallamach-type wavy pattern. The blends HNBR-FKM and HNBR-CBT were two-phase structured. In HNBR-FKM, the FKM was dispersed in form of large microscaled domains in the HNBR matrix. This phase structure did not change by incorporation of MWCNT. It was established that the MWCNT was preferentially embedded in the HNBR matrix. Blending HNBR with FKM reduced the stiffness and degree of apparent crosslinking of the blend, which was traced to the dilution of the cure recipe with FKM. The coefficient of friction increased with increasing FKM opposed to the expectation. On the other hand, the specific wear rate (Ws) changed marginally with increasing content of FKM. In HNBR-CBT hybrids the HNBR was the matrix, irrespective to the rather high CBT content. Both the partly and mostly polymerized CBT ((p)CBT and pCBT, respectively) in the hybrids worked as active filler and thus increased the stiffness and hardness. The COF and Ws decreased with increasing CBT content. The FEM results in respect to COF achieved on systems possessing very different structures and thus properties (EPDM_30CB, HNBR-FKM 100-100 and HNBR-(p)CBT 100-100, respectively) were in accordance with the experimental results. This verifies that FEM can be properly used to consider the complex viscoelastic behaviour of rubber materials under dry rolling condition.

This paper discusses the problem of automatic off-line programming and motion planning for industrial robots. At first, a new concept consisting of three steps is proposed. The first step, a new method for on-line motion planning is introduced. The motion planning method is based on the A*-search algorithm and works in the implicit configuration space. During searching, the collisions are detected in the explicitly represented Cartesian workspace by hierarchical distance computation. In the second step, the trajectory planner has to transform the path into a time and energy optimal robot program. The practical application of these two steps strongly depends on the method for robot calibration with high accuracy, thus, mapping the virtual world onto the real world, which is discussed in the third step.

This paper presents a new approach to parallel motion planning for industrial robot arms with six degrees of freedom in an on-line given 3D environment. The method is based on the A-search algorithm and needs no essential off-line computations. The algorithm works in an implicitly descrete configuration space. Collisions are detected in the Cartesian workspace by hierarchical distance computation based on the given CAD model. By decomposing the 6D configuration space into hypercubes and cyclically mapping them onto multiple processing units, a good load distribution can be achieved. We have implemented the parallel motion planner on a workstation cluster with 9 PCs and tested the planner for several benchmark environments. With optimal discretisation, the new approach usually shows linear speedups. In on-line provided environments with static obstacles, the parallel planning times are only a few seconds.

A practical distributed planning and control system for industrial robots is presented. The hierarchical concept consists of three independent levels. Each level is modularly implemented and supplies an application interface (API) to the next higher level. At the top level, we propose an automatic motion planner. The motion planner is based on a best-first search algorithm and needs no essential off-line computations. At the middle level, we propose a PC-based robot control architecture, which can easily be adapted to any industrial kinematics and application. Based on a client/server-principle, the control unit estab-lishes an open user interface for including application specific programs. At the bottom level, we propose a flexible and modular concept for the integration of the distributed motion control units based on the CAN bus. The concept allows an on-line adaptation of the control parameters according to the robot's configuration. This implies high accuracy for the path execution and improves the overall system performance.

A new problem for the automated off-line programming of industrial robot application is investigated. The Multi-Goal Path Planning is to find the collision-free path connecting a set of goal poses and minimizing e.g. the total path length. Our solution is based on an earlier reported path planner for industrial robot arms with 6 degrees-of-freedom in an on-line given 3D environment. To control the path planner, four different goal selection methods are introduced and compared. While the Random and the Nearest Pair Selection methods can be used with any path planner, the Nearest Goal and the Adaptive Pair Selection method are favorable for our planner. With the latter two goal selection methods, the Multi-Goal Path Planning task can be significantly accelerated, because they are able to automatically solve the simplest path planning problems first. Summarizing, compared to Random or Nearest Pair Selection, this new Multi-Goal Path Planning approach results in a further cost reduction of the programming phase.

This paper presents a new approach to parallel motion planning for industrial robot arms with six degrees of freedom in an on-line given 3D environment. The method is based on the A*-search algorithm and needs no essential off-line computations. The algorithm works in an implicitly descrete configuration space. Collisions are detected in the cartesian workspace by hierarchical distance computation based on the given CAD model. By decomposing the 6D configuration space into hypercubes and cyclically mapping them onto multiple processing units, a good load distribution can be achieved. We have implemented the parallel motion planner on a workstation cluster with 9 PCs and tested the planner for several benchmark environments. With optimal discretisation, the new approach usually shows linear, and sometimes even superlinear speedups. In on-line provided environments with static obstacles, the parallel planning times are only a few seconds.

This article presents contributions in the field of path planning for industrial robots with 6 degrees of freedom. This work presents the results of our research in the last 4 years at the Institute for Process Control and Robotics at the University of Karlsruhe. The path planning approach we present works in an implicit and discretized C-space. Collisions are detected in the Cartesian workspace by a hierarchical distance computation. The method is based on the A* search algorithm and needs no essential off-line computation. A new optimal discretization method leads to smaller search spaces, thus speeding up the planning. For a further acceleration, the search was parallelized. With a static load distribution good speedups can be achieved. By extending the algorithm to a bidirectional search, the planner is able to automatically select the easier search direction. The new dynamic switching of start and goal leads finally to the multi-goal path planning, which is able to compute a collision-free path between a set of goal poses (e.g., spot welding points) while minimizing the total path length.

The objective of this thesis consists in developing systematic event-triggered control designs for specified event generators, which is an important alternative to the traditional periodic sampling control. Sporadic sampling inherently arising in event-triggered control is determined by the event-triggering conditions. This feature invokes the desire of
finding new control theory as the traditional sampled-data theory in computer control.
Developing controller coupling with the applied event-triggering condition to maximize the control performance is the essence for event-triggered control design. In the design the stability of the control system needs to be ensured with the first priority. Concerning variant control aims they should be clearly incorporated in the design procedures. Considering applications in embedded control systems efficient implementation requires a low complexity of embedded software architectures. The thesis targets at offering such a design to further complete the theory of event-triggered control designs.

An interrupter for use in a daisy-chained VME bus interrupt system has beendesigned and implemented as an asynchronous sequential circuit. The concur-rency of the processes posed a design problem that was solved by means of asystematic design procedure that uses Petri nets for specifying system and in-terrupter behaviour, and for deriving a primitive flow table. Classical designand additional measures to cope with non-fundamental mode operation yieldeda coded state-machine representation. This was implemented on a GAL 22V10,chosen for its hazard-preventing structure and for rapid prototyping in studentlaboratories.

On the Complexity of the Uncapacitated Single Allocation p-Hub Median Problem with Equal Weights
(2007)

The Super-Peer Selection Problem is an optimization problem in network topology construction. It may be cast as a special case of a Hub Location Problem, more exactly an Uncapacitated Single Allocation p-Hub Median Problem with equal weights. We show that this problem is still NP-hard by reduction from Max Clique.

Phase velocities of surface acoustic waves in several boron nitride films were investigated by Brillouin light scattering. In the case of films with predominantly hexagonal crystal structure, grown under conditions close to the nucleation threshold of cubic BN, four independent elastic constants have been determined from the dispersion of the Rayleigh and the first Sezawa mode. The large elastic anisotropy of up to c11/c33 = 0.1 is attributed to a pronounced texture with the c-axes of the crystallites parallel to the film plane. In the case of cubic BN films the dispersion of the Rayleigh wave provides evidence for the existence of a more compliant layer at the substrate-film interface. The observed broadening of the Rayleigh mode is identified to be caused by the film morphology.

Hexagonal BN films have been deposited by rf-magnetron sputtering with simultaneous ion plating. The elastic properties of the films grown on silicon substrates under identical coating conditions have been de-termined by Brillouin light scattering from thermally excited surface phonons. Four of the five independent elastic constants of the deposited material are found to be c11 = 65 GPa, c13 = 7 GPa, c33 = 92 GPa and c44 = 53 GPa exhibiting an elastic anisotropy c11/c33 of 0.7. The Young's modulus determined with load indenta-tion is distinctly larger than the corresponding value taken from Brillouin light scattering. This discrepancy is attributed to the specific morphology of the material with nanocrystallites embedded in an amorphous matrix.

A Topology Primer
(2002)

Manifolds
(2017)

We present a convenient notation for positive/negativeADconditional equations. Theidea is to merge rules specifying the same function by using caseAD, ifAD, matchAD, and letADexpressions.Based on the presented macroADruleADconstruct, positive/negativeADconditional equational specifiADcations can be written on a higher level. A rewrite system translates the macroADruleADconstructsinto positive/negativeADconditional equations.

We present an inference system for clausal theorem proving w.r.t. various kinds of inductivevalidity in theories specified by constructor-based positive/negative-conditional equations. The reductionrelation defined by such equations has to be (ground) confluent, but need not be terminating. Our con-structor-based approach is well-suited for inductive theorem proving in the presence of partially definedfunctions. The proposed inference system provides explicit induction hypotheses and can be instantiatedwith various wellfounded induction orderings. While emphasizing a well structured clear design of theinference system, our fundamental design goal is user-orientation and practical usefulness rather thantheoretical elegance. The resulting inference system is comprehensive and relatively powerful, but requiresa sophisticated concept of proof guidance, which is not treated in this paper.This research was supported by the Deutsche Forschungsgemeinschaft, SFB 314 (D4-Projekt)

We study the combination of the following already known ideas for showing confluence ofunconditional or conditional term rewriting systems into practically more useful confluence criteria forconditional systems: Our syntactic separation into constructor and non-constructor symbols, Huet's intro-duction and Toyama's generalization of parallel closedness for non-noetherian unconditional systems, theuse of shallow confluence for proving confluence of noetherian and non-noetherian conditional systems, theidea that certain kinds of limited confluence can be assumed for checking the fulfilledness or infeasibilityof the conditions of conditional critical pairs, and the idea that (when termination is given) only primesuperpositions have to be considered and certain normalization restrictions can be applied for the sub-stitutions fulfilling the conditions of conditional critical pairs. Besides combining and improving alreadyknown methods, we present the following new ideas and results: We strengthen the criterion for overlayjoinable noetherian systems, and, by using the expressiveness of our syntactic separation into constructorand non-constructor symbols, we are able to present criteria for level confluence that are not criteria forshallow confluence actually and also able to weaken the severe requirement of normality (stiffened withleft-linearity) in the criteria for shallow confluence of noetherian and non-noetherian conditional systems tothe easily satisfied requirement of quasi-normality. Finally, the whole paper also gives a practically usefuloverview of the syntactic means for showing confluence of conditional term rewriting systems.

Modern digital imaging technologies, such as digital microscopy or micro-computed tomography, deliver such large amounts of 2D and 3D-image data that manual processing becomes infeasible. This leads to a need for robust, flexible and automatic image analysis tools in areas such as histology or materials science, where microstructures are being investigated (e.g. cells, fiber systems). General-purpose image processing methods can be used to analyze such microstructures. These methods usually rely on segmentation, i.e., a separation of areas of interest in digital images. As image segmentation algorithms rarely adapt well to changes in the imaging system or to different analysis problems, there is a demand for solutions that can easily be modified to analyze different microstructures, and that are more accurate than existing ones. To address these challenges, this thesis contributes a novel statistical model for objects in images and novel algorithms for the image-based analysis of microstructures. The first contribution is a novel statistical model for the locations of objects (e.g. tumor cells) in images. This model is fully trainable and can therefore be easily adapted to many different image analysis tasks, which is demonstrated by examples from histology and materials science. Using algorithms for fitting this statistical model to images results in a method for locating multiple objects in images that is more accurate and more robust to noise and background clutter than standard methods. On simulated data at high noise levels (peak signal-to-noise ratio below 10 dB), this method achieves detection rates up to 10% above those of a watershed-based alternative algorithm. While objects like tumor cells can be described well by their coordinates in the plane, the analysis of fiber systems in composite materials, for instance, requires a fully three dimensional treatment. Therefore, the second contribution of this thesis is a novel algorithm to determine the local fiber orientation in micro-tomographic reconstructions of fiber-reinforced polymers and other fibrous materials. Using simulated data, it will be demonstrated that the local orientations obtained from this novel method are more robust to noise and fiber overlap than those computed using an established alternative gradient-based algorithm, both in 2D and 3D. The property of robustness to noise of the proposed algorithm can be explained by the fact that a low-pass filter is used to detect local orientations. But even in the absence of noise, depending on fiber curvature and density, the average local 3D-orientation estimate can be about 9° more accurate compared to that alternative gradient-based method. Implementations of that novel orientation estimation method require repeated image filtering using anisotropic Gaussian convolution filters. These filter operations, which other authors have used for adaptive image smoothing, are computationally expensive when using standard implementations. Therefore, the third contribution of this thesis is a novel optimal non-orthogonal separation of the anisotropic Gaussian convolution kernel. This result generalizes a previous one reported elsewhere, and allows for efficient implementations of the corresponding convolution operation in any dimension. In 2D and 3D, these implementations achieve an average performance gain by factors of 3.8 and 3.5, respectively, compared to a fast Fourier transform-based implementation. The contributions made by this thesis represent improvements over state-of-the-art methods, especially in the 2D-analysis of cells in histological resections, and in the 2D and 3D-analysis of fibrous materials.

This report reviews selected image binarization and segmentation methods that have been proposed and which are suitable for the processing of volume images. The focus is on thresholding, region growing, and shape–based methods. Rather than trying to give a complete overview of the field, we review the original ideas and concepts of selected methods, because we believe this information to be important for judging when and under what circumstances a segmentation algorithm can be expected to work properly.

We consider a volume maximization problem arising in gemstone cutting industry. The problem is formulated as a general semi-infinite program (GSIP) and solved using an interiorpoint method developed by Stein. It is shown, that the convexity assumption needed for the convergence of the algorithm can be satisfied by appropriate modelling. Clustering techniques are used to reduce the number of container constraints, which is necessary to make the subproblems practically tractable. An iterative process consisting of GSIP optimization and adaptive refinement steps is then employed to obtain an optimal solution which is also feasible for the original problem. Some numerical results based on realworld data are also presented.

The thesis at hand deals with the numerical solution of multiscale problems arising in the modeling of processes in fluid and thermo dynamics. Many of these processes, governed by partial differential equations, are relevant in engineering, geoscience, and environmental studies. More precisely, this thesis discusses the efficient numerical computation of effective macroscopic thermal conductivity tensors of high-contrast composite materials. The term "high-contrast" refers to large variations in the conductivities of the constituents of the composite. Additionally, this thesis deals with the numerical solution of Brinkman's equations. This system of equations adequately models viscous flows in (highly) permeable media. It was introduced by Brinkman in 1947 to reduce the deviations between the measurements for flows in such media and the predictions according to Darcy's model.

Wireless sensor networks are the driving force behind many popular and interdisciplinary research areas, such as environmental monitoring, building automation, healthcare and assisted living applications. Requirements like compactness, high integration of sensors, flexibility, and power efficiency are often very different and cannot be fulfilled by state-of-the-art node platforms at once. In this paper, we present and analyze AmICA: a flexible, compact, easy-to-program, and low-power node platform. Developed from scratch and including a node, a basic communication protocol, and a debugging toolkit, it assists in an user-friendly rapid application development. The general purpose nature of AmICA was evaluated in two practical applications with diametric requirements. Our analysis shows that AmICA nodes are 67% smaller than BTnodes, have five times more sensors than Mica2Dot and consume 72% less energy than the state-of-the-art TelosB mote in sleep mode.

INRECA offers tools and methods for developing, validating, and maintaining classification, diagnosis and decision support systems. INRECA's basic technologies are inductive and case-based reasoning [9]. INRECA fully integrates [2] both techniques within one environment and uses the respective advantages of both technologies. Its object-oriented representation language CASUEL [10, 3] allows the definition of complex case structures, relations, similarity measures, as well as background knowledge to be used for adaptation. The objectoriented representation language makes INRECA a domain independent tool for its destined kind of tasks. When problems are solved via case-based reasoning, the primary kind of knowledge that is used during problem solving is the very specific knowledge contained in the cases. However, in many situations this specific knowledge by itself is not sufficient or appropriate to cope with all requirements of an application. Very often, background knowledge is available and/or necessary to better explore and interpret the available cases [1]. Such general knowledge may state dependencies between certain case features and can be used to infer additional, previously unknown features from the known ones.

Most of today’s wireless communication devices operate on unlicensed bands with uncoordinated spectrum access, with the consequence that RF interference and collisions are impairing the overall performance of wireless networks. In the classical design of network protocols, both packets in a collision are considered lost, such that channel access mechanisms attempt to avoid collisions proactively. However, with the current proliferation of wireless applications, e.g., WLANs, car-to-car networks, or the Internet of Things, this conservative approach is increasingly limiting the achievable network performance in practice. Instead of shunning interference, this thesis questions the notion of „harmful“ interference and argues that interference can, when generated in a controlled manner, be used to increase the performance and security of wireless systems. Using results from information theory and communications engineering, we identify the causes for reception or loss of packets and apply these insights to design system architectures that benefit from interference. Because the effect of signal propagation and channel fading, receiver design and implementation, and higher layer interactions on reception performance is complex and hard to reproduce by simulations, we design and implement an experimental platform for controlled interference generation to strengthen our theoretical findings with experimental results. Following this philosophy, we introduce and evaluate a system architecture that leverage interference.
First, we identify the conditions for successful reception of concurrent transmissions in wireless networks. We focus on the inherent ability of angular modulation receivers to reject interference when the power difference of the colliding signals is sufficiently large, the so-called capture effect. Because signal power fades over distance, the capture effect enables two or more sender–receiver pairs to transmit concurrently if they are positioned appropriately, in turn boosting network performance. Second, we show how to increase the security of wireless networks with a centralized network access control system (called WiFire) that selectively interferes with packets that violate a local security policy, thus effectively protecting legitimate devices from receiving such packets. WiFire’s working principle is as follows: a small number of specialized infrastructure devices, the guardians, are distributed alongside a network and continuously monitor all packet transmissions in the proximity, demodulating them iteratively. This enables the guardians to access the packet’s content before the packet fully arrives at the receiver. Using this knowledge the guardians classify the packet according to a programmable security policy. If a packet is deemed malicious, e.g., because its header fields indicate an unknown client, one or more guardians emit a limited burst of interference targeting the end of the packet, with the objective to introduce bit errors into it. Established communication standards use frame check sequences to ensure that packets are received correctly; WiFire leverages this built-in behavior to prevent a receiver from processing a harmful packet at all. This paradigm of „over-the-air“ protection without requiring any prior modification of client devices enables novel security services such as the protection of devices that cannot defend themselves because their performance limitations prohibit the use of complex cryptographic protocols, or of devices that cannot be altered after deployment.
This thesis makes several contributions. We introduce the first software-defined radio based experimental platform that is able to generate selective interference with the timing precision needed to evaluate the novel architectures developed in this thesis. It implements a real-time receiver for IEEE 802.15.4, giving it the ability to react to packets in a channel-aware way. Extending this system design and implementation, we introduce a security architecture that enables a remote protection of wireless clients, the wireless firewall. We augment our system with a rule checker (similar in design to Netfilter) to enable rule-based selective interference. We analyze the security properties of this architecture using physical layer modeling and validate our analysis with experiments in diverse environmental settings. Finally, we perform an analysis of concurrent transmissions. We introduce a new model that captures the physical properties correctly and show its validity with experiments, improving the state of the art in the design and analysis of cross-layer protocols for wireless networks.

It has been observed that for understanding the biological function of certain RNA molecules, one has to study joint secondary structures of interacting pairs of RNA. In this thesis, a new approach for predicting the joint structure is proposed and implemented. For this, we introduce the class of m-dimensional context-free grammars --- an extension of stochastic context-free grammars to multiple dimensions --- and present an Earley-style semiring parser for this class. Additionally, we develop and thoroughly discuss an implementation variant of Earley parsers tailored to efficiently handle dense grammars, which embraces the grammars used for structure prediction. A currently proposed partitioning scheme for joint secondary structures is transferred into a two-dimensional context-free grammar, which in turn is used as a stochastic model for RNA-RNA interaction. This model is trained on actual data and then used for predicting most likely joint structures for given RNA molecules. While this technique has been widely used for secondary structure prediction of single molecules, RNA-RNA interaction was hardly approached this way in the past. Although our parser has O(n^3 m^3) time complexity and O(n^2 m^2) space complexity for two RNA molecules of sizes n and m, it remains practically applicable for typical sizes if enough memory is available. Experiments show that our parser is much more efficient for this application than classical Earley parsers. Moreover the predictions of joint structures are comparable in quality to current energy minimization approaches.

Recently, a new Quicksort variant due to Yaroslavskiy was chosen as standard sorting
method for Oracle's Java 7 runtime library. The decision for the change was based on
empirical studies showing that on average, the new algorithm is faster than the formerly
used classic Quicksort. Surprisingly, the improvement was achieved by using a dual pivot
approach — an idea that was considered not promising by several theoretical studies in the
past. In this thesis, I try to find the reason for this unexpected success.
My focus is on the precise and detailed average case analysis, aiming at the flavor of
Knuth's series “The Art of Computer Programming”. In particular, I go beyond abstract
measures like counting key comparisons, and try to understand the efficiency of the
algorithms at different levels of abstraction. Whenever possible, precise expected values are
preferred to asymptotic approximations. This rigor ensures that (a) the sorting methods
discussed here are actually usable in practice and (b) that the analysis results contribute to
a sound comparison of the Quicksort variants.

Dual-Pivot Quicksort and Beyond: Analysis of Multiway Partitioning and Its Practical Potential
(2016)

Multiway Quicksort, i.e., partitioning the input in one step around several pivots, has received much attention since Java 7’s runtime library uses a new dual-pivot method that outperforms by far the old Quicksort implementation. The success of dual-pivot Quicksort is most likely due to more efficient usage of the memory hierarchy, which gives reason to believe that further improvements are possible with multiway Quicksort.
In this dissertation, I conduct a mathematical average-case analysis of multiway Quicksort including the important optimization to choose pivots from a sample of the input. I propose a parametric template algorithm that covers all practically relevant partitioning methods as special cases, and analyze this method in full generality. This allows me to analytically investigate in depth what effect the parameters of the generic Quicksort have on its performance. To model the memory-hierarchy costs, I also analyze the expected number of scanned elements, a measure for the amount of data transferred from memory that is known to also approximate the number of cache misses very well. The analysis unifies previous analyses of particular Quicksort variants under particular cost measures in one generic framework.
A main result is that multiway partitioning can reduce the number of scanned elements significantly, while it does not save many key comparisons; this explains why the earlier studies of multiway Quicksort did not find it promising. A highlight of this dissertation is the extension of the analysis to inputs with equal keys. I give the first analysis of Quicksort with pivot sampling and multiway partitioning on an input model with equal keys.

In the first part of the thesis we develop the theory of standard bases in free modules over (localized) polynomial rings. Given that linear equations are solvable in the coefficients of the polynomials, we introduce an algorithm to compute standard bases with respect to arbitrary (module) monomial orderings. Moreover, we take special care to principal ideal rings, allowing zero divisors. For these rings we design modified algorithms which are new and much faster than the general ones. These algorithms were motivated by current limitations in formal verification of microelectronic System-on-Chip designs. We show that our novel approach using computational algebra is able to overcome these limitations in important classes of applications coming from industrial challenges.
The second part is based on research in collaboration with Jason Morton, Bernd Sturmfels and Anne Shiu. We devise a general method to describe and compute a certain class of rank tests motivated by statistics. The class of rank tests may loosely be described as being based on computing the number of linear extensions to given partial orders. In order to apply these tests to actual data we developed two algorithms and used our implementations to apply the methodology to gene expression data created at the Stowers Institute for Medical Research. The dataset is concerned with the development of the vertebra. Our rankings proved valuable to the biologists.

The stationary heat equation is solved with periodic boundary conditions in geometrically complex composite materials with high contrast in the thermal conductivities of the individual phases. This is achieved by harmonic averaging and explicitly introducing the jumps across the material interfaces as additional variables. The continuity of the heat flux yields the needed extra equations for these variables. A Schur-complent formulation for the new variables is derived that is solved using the FFT and BiCGStab methods. The EJ-HEAT solver is given as a 3-page Matlab program in the Appendix. The C++ implementation is used for material design studies. It solves 3-dimensional problems with around 190 Mio variables on a 64-bit AMD Opteron desktop system in less than 6 GB memory and in minutes to hours, depending on the contrast and required accuracy. The approach may also be used to compute effective electric conductivities because they are governed by the stationary heat equation.

Four aspects are important in the design of hydraulic lters. We distinguish between two cost factors and two performance factors. Regarding performance, filter eciencynd lter capacity are of interest. Regarding cost, there are production considerations such as spatial restrictions, material cost and the cost of manufacturing the lter. The second type of cost is the operation cost, namely the pressure drop. Albeit simulations should and will ultimately deal with all 4 aspects, for the moment our work is focused on cost. The PleatGeo Module generates three-dimensional computer models of a single pleat of a hydraulic lter interactively. PleatDict computes the pressure drop that will result for the particular design by direct numerical simulation. The evaluation of a new pleat design takes only a few hours on a standard PC compared to days or weeks used for manufacturing and testing a new prototype of a hydraulic lter. The design parameters are the shape of the pleat, the permeabilities of one or several layers of lter media and the geometry of a supporting netting structure that is used to keep the out ow area open. Besides the underlying structure generation and CFD technology, we present some trends regarding the dependence of pressure drop on design parameters that can serve as guide lines for the design of hydraulic lters. Compared to earlier two-dimensional models, the three-dimensional models can include a support structure.

A fully automatic procedure is proposed to rapidly compute the permeability of porous materials from their binarized microstructure. The discretization is a simplified version of Peskin’s Immersed Boundary Method, where the forces are applied at the no-slip grid points. As needed for the computation of permeability, steady flows at zero Reynolds number are considered. Short run-times are achieved by eliminating the pressure and velocity variables using an Fast Fourier Transform-based and 4 Poisson problembased fast inversion approach on rectangular parallelepipeds with periodic boundary conditions. In reference to calling it a fast method using fictitious or artificial forces, the implementation is called FFF-Stokes. Large scale computations on 3d images are quickly and automatically performed to estimate the permeability of some sample materials. A matlab implementation is provided to allow readers to experience the automation and speed of the method for realistic three-dimensional models.

Model uncertainty is a challenge that is inherent in many applications of mathematical models in various areas, for instance in mathematical finance and stochastic control. Optimization procedures in general take place under a particular model. This model, however, might be misspecified due to statistical estimation errors and incomplete information. In that sense, any specified model must be understood as an approximation of the unknown "true" model. Difficulties arise since a strategy which is optimal under the approximating model might perform rather bad in the true model. A natural way to deal with model uncertainty is to consider worst-case optimization.
The optimization problems that we are interested in are utility maximization problems in continuous-time financial markets. It is well known that drift parameters in such markets are notoriously difficult to estimate. To obtain strategies that are robust with respect to a possible misspecification of the drift we consider a worst-case utility maximization problem with ellipsoidal uncertainty sets for the drift parameter and with a constraint on the strategies that prevents a pure bond investment.
By a dual approach we derive an explicit representation of the optimal strategy and prove a minimax theorem. This enables us to show that the optimal strategy converges to a generalized uniform diversification strategy as uncertainty increases.
To come up with a reasonable uncertainty set, investors can use filtering techniques to estimate the drift of asset returns based on return observations as well as external sources of information, so-called expert opinions. In a Black-Scholes type financial market with a Gaussian drift process we investigate the asymptotic behavior of the filter as the frequency of expert opinions tends to infinity. We derive limit theorems stating that the information obtained from observing the discrete-time expert opinions is asymptotically the same as that from observing a certain diffusion process which can be interpreted as a continuous-time expert. Our convergence results carry over to convergence of the value function in a portfolio optimization problem with logarithmic utility.
Lastly, we use our observations about how expert opinions improve drift estimates for our robust utility maximization problem. We show that our duality approach carries over to a financial market with non-constant drift and time-dependence in the uncertainty set. A time-dependent uncertainty set can then be defined based on a generic filter. We apply this to various investor filtrations and investigate which effect expert opinions have on the robust strategies.

In the presented work, I evaluate if and how Virtual Reality (VR) technologies can be used to support researchers working in the geosciences by providing immersive, collaborative visualization systems as well as virtual tools for data analysis. Technical challenges encountered in the development of theses systems are identified and solutions for these are provided.
To enable geologists to explore large digital terrain models (DTMs) in an immersive, explorative fashion within a VR environment, a suitable terrain rendering algorithm is required. For realistic perception of planetary curvature at large viewer altitudes, spherical rendering of the surface is necessary. Furthermore, rendering must sustain interactive frame rates of about 30 frames per second to avoid sensory confusion of the user. At the same time, the data structures used for visualization should also be suitable for efficiently computing spatial properties such as height profiles or volumes in order to implement virtual analysis tools. To address these requirements, I have developed a novel terrain rendering algorithm based on tiled quadtree hierarchies using the HEALPix parametrization of a sphere. For evaluation purposes, the system is applied to a 500 GiB dataset representing the surface of Mars.
Considering the current development of inexpensive remote surveillance equipment such as quadcopters, it seems inevitable that these devices will play a major role in future disaster management applications. Virtual reality installations in disaster management headquarters which provide an immersive visualization of near-live, three-dimensional situational data could then be a valuable asset for rapid, collaborative decision making. Most terrain visualization algorithms, however, require a computationally expensive pre-processing step to construct a terrain database.
To address this problem, I present an on-the-fly pre-processing system for cartographic data. The system consists of a frontend for rendering and interaction as well as a distributed processing backend executing on a small cluster which produces tiled data in the format required by the frontend on demand. The backend employs a CUDA based algorithm on graphics cards to perform efficient conversion from cartographic standard projections to the HEALPix-based grid used by the frontend.
Measurement of spatial properties is an important step in quantifying geological phenomena. When performing these tasks in a VR environment, a suitable input device and abstraction for the interaction (a “virtual tool”) must be provided. This tool should enable the user to precisely select the location of the measurement even under a perspective projection. Furthermore, the measurement process should be accurate to the resolution of the data available and should not have a large impact on the frame rate in order to not violate interactivity requirements.
I have implemented virtual tools based on the HEALPix data structure for measurement of height profiles as well as volumes. For interaction, a ray-based picking metaphor was employed, using a virtual selection ray extending from the user’s hand holding a VR interaction device. To provide maximum accuracy, the algorithms access the quad-tree terrain database at the highest available resolution level while at the same time maintaining interactivity in rendering.
Geological faults are cracks in the earth’s crust along which a differential movement of rock volumes can be observed. Quantifying the direction and magnitude of such translations is an essential requirement in understanding earth’s geological history. For this purpose, geologists traditionally use maps in top-down projection which are cut (e.g. using image editing software) along the suspected fault trace. The two resulting pieces of the map are then translated in parallel against each other until surface features which have been cut by the fault motion come back into alignment. The amount of translation applied is then used as a hypothesis for the magnitude of the fault action. In the scope of this work it is shown, however, that performing this study in a top-down perspective can lead to the acceptance of faulty reconstructions, since the three-dimensional structure of topography is not considered.
To address this problem, I present a novel terrain deformation algorithm which allows the user to trace a fault line directly within a 3D terrain visualization system and interactively deform the terrain model while inspecting the resulting reconstruction from arbitrary perspectives. I demonstrate that the application of 3D visualization allows for a more informed interpretation of fault reconstruction hypotheses. The algorithm is implemented on graphics cards and performs real-time geometric deformation of the terrain model, guaranteeing interactivity with respect to all parameters.
Paleoceanography is the study of the prehistoric evolution of the ocean. One of the key data sources used in this research are coring experiments which provide point samples of layered sediment depositions at the ocean floor. The samples obtained in these experiments document the time-varying sediment concentrations within the ocean water at the point of measurement. The task of recovering the ocean flow patterns based on these deposition records is a challenging inverse numerical problem, however.
To support domain scientists working on this problem, I have developed a VR visualization tool to aid in the verification of model parameters by providing simultaneous visualization of experimental data from coring as well as the resulting predicted flow field obtained from numerical simulation. Earth is visualized as a globe in the VR environment with coring data being presented using a billboard rendering technique while the
time-variant flow field is indicated using Line-Integral-Convolution (LIC). To study individual sediment transport pathways and their correlation with the depositional record, interactive particle injection and real-time advection is supported.

In this dissertation we consider complex, projective hypersurfaces with many isolated singularities. The leading questions concern the maximal number of prescribed singularities of such hypersurfaces in a given linear system, and geometric properties of the equisingular stratum. In the first part a systematic introduction to the theory of equianalytic families of hypersurfaces is given. Furthermore, the patchworking method for constructing hypersurfaces with singularities of prescribed types is described. In the second part we present new existence results for hypersurfaces with many singularities. Using the patchworking method, we show asymptotically proper results for hypersurfaces in P^n with singularities of corank less than two. In the case of simple singularities, the results are even asymptotically optimal. These statements improve all previous general existence results for hypersurfaces with these singularities. Moreover, the results are also transferred to hypersurfaces defined over the real numbers. The last part of the dissertation deals with the Castelnuovo function for studying the cohomology of ideal sheaves of zero-dimensional schemes. Parts of the theory of this function for schemes in P^2 are generalized to the case of schemes on general surfaces in P^3. As an application we show an H^1-vanishing theorem for such schemes.

We describe a hybrid architecture supporting planning for machining workpieces. The archi- tecture is built around CAPlan, a partial-order nonlinear planner that represents the plan already generated and allows external control decision made by special purpose programs or by the user. To make planning more efficient, the domain is hierarchically modelled. Based on this hierarchical representation, a case-based control component has been realized that allows incremental acquisition of control knowledge by storing solved problems and reusing them in similar situations.