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Skript zur Vorlesung "Character Theory of finite groups".
This thesis is concerned with the modeling of the solid-solid phase transformation, such as the martensitic transformation. The allotropes austenite and martensite are important for industry applications. As a result of its ductility, austenite is desired in the bulk, as opposed to martensite, which desired in the near surface region. The phase field method is used to model the phase transformation by minimizing the free energy. It consists of a mechanical part, due to elastic strain and a chemical part, due to the martensitic transformation. The latter is temperature dependent. Therefore, a temperature dependent separation potential is presented here. To accommodate multiple orientation variants, a multivariant phase field model is employed. Using the Khachaturyan approach, the effective material parameters can be used to describe a constitutive model. This however, renders the nodal residual vector and elemental tangent matrix directly dependent on the phase, making a generalization complicated. An easier approach is the use of the Voigt/Taylor homogenization, in which the energy and their derivatives are interpolated creating an interface for material law of the individual phases.
Scaling up conventional processor architectures cannot translate the ever-increasing number of transistors into comparable application performance. Although the trend is to shift from single-core to multi-core architectures, utilizing these multiple cores is not a trivial task for many applications due to thread synchronization and weak memory consistency issues. This is especially true for applications in real-time embedded systems since timing analysis becomes more complicated due to contention on shared resources. One inherent reason for the limited use of instruction-level parallelism (ILP) by conventional processors is the use of registers. Therefore, some recent processors bypass register usage by directly communicating values from producer processing units to consumer processing units. In widely used superscalar processors, this direct instruction communication is organized by hardware at runtime, adversely affecting its scalability. The exposed datapath architectures provide a scalable alternative by allowing compilers to move values directly from output ports to the input ports of processing units. Though exposed datapath architectures have already been studied in great detail, they still use registers for executing programs, thus limiting the amount of ILP they can exploit. This limitation stems from a drawback in their execution paradigm, code generator, or both.
This thesis considers a novel exposed datapath architecture named Synchronous Control Asynchronous Dataflow (SCAD) that follows a hybrid control-flow dataflow execution paradigm. The SCAD architecture employs first-in-first-out (FIFO) buffers at the output and input ports of processing units. It is programmed by move instructions that transport values from the head of output buffers to the tail of input buffers. Thus, direct instruction communication is facilitated by the architecture. The processing unit triggers the execution of an operation when operand values are available at the heads of its input buffers. We propose a code generation technique for SCAD processors inspired by classical queue machines that completely eliminates the use of registers. On this basis, we first generate optimal code by using satisfiability (SAT) solvers after establishing that optimal code generation is hard. Heuristics based on a novel buffer interference analysis are then developed to compile larger programs. The experimental results demonstrate the efficacy of the execution paradigm of SCAD using our queue-oriented code generation technique.
Mixed-mode chromatography (MMC), which combines features of ion exchange chromatography (IEC) and hydrophobic interaction chromatography (HIC), is an interesting method for protein separation and purification. The design of MMC processes is challenging as adsorption equilibria are influenced by many parameters, including ionic strength and the presence of different salts in solution. Systematic studies on the influence of those parameters in MMC are rare. Therefore, in the present work, the influence of four salts, namely, sodium chloride, sodium sulfate, ammonium chloride, and ammonium sulfate, on the adsorption of lysozyme on the mixed-mode resin Toyopearl MX-Trp-650M at pH 7.0 and 25°C was studied systematically in equilibrium adsorption experiments for ionic strengths between 0 mM and 3000 mM. For all salts, a noticeable adsorption strength was observed over the entire range of studied ionic strengths. An exponential decay of the loading of the resin with increasing ionic strength was found until approx. 1000 mM. For higher ionic strengths, the loading was found to be practically independent of the ionic strength. At constant ionic strength, the highest lysozyme loadings were observed for ammonium sulfate, the lowest for sodium chloride. A mathematical model was developed that correctly describes the influence of the ionic strength as well as the influence of the studied salts. The model is the first that enables the prediction of adsorption isotherms of proteins on mixed-mode resins in a wide range of technically interesting conditions, accounting for the influence of the ionic strength and four salts of practical relevance.
In recent years, business intelligence applications become more real-time and traditional data warehouse tables become fresher as they are continuously refreshed by streaming ETL jobs within seconds. Besides, a new type of federated system emerged that unifies domain-specific computation engines to address a wide range of complex analytical applications, which needs streaming ETL to migrate data across computation systems.
From daily-sales reports to up-to-the-second cross-/up-sell campaign activities, we observed various latency and freshness requirements set in these analytical applications. Hence, streaming ETL jobs with regular batches are not flexible enough to fit in such a mixed workload. Jobs with small batches can cause resource overprovision for queries with low freshness needs while jobs with large batches would starve queries with high freshness needs. Therefore, we argue that ETL jobs should be self-adaptive to varying SLA demands by setting appropriate batches as needed.
The major contributions are summarized as follows.
• We defined a consistency model for “On-Demand ETL” which addresses correct batches for queries to see consistent states. Furthermore, we proposed an “Incremental ETL Pipeline” which reduces the performance impact of on-demand ETL processing.
• A distributed, incremental ETL pipeline (called HBelt) was introduced in distributed warehouse systems. HBelt aims at providing consistent, distributed snapshot maintenance for concurrent table scans across different analytics jobs.
• We addressed the elasticity property for incremental ETL pipeline to guarantee that ETL jobs with batches of varying sizes can be finished within strict deadlines. Hence, we proposed Elastic Queue Middleware and HBaqueue which replace memory-based data exchange queues with a scalable distributed store - HBase.
• We also implemented lazy maintenance logic in the extraction and the loading phases to make these two phases workload-aware. Besides, we discuss how our “On-Demand ETL” thinking can be exploited in analytic flows running on heterogeneous execution engines.
Simplified ODE models describing blood flow rate are governed by the pressure gradient.
However, assuming the orientation of the blood flow in a human body correlates to a positive
direction, a negative pressure gradient forces the valve to shut, which stops the flow through
the valve, hence, the flow rate is zero, whereas the pressure rate is formulated by an ODE.
Presence of ODEs together with algebraic constraints and sudden changes of system characterizations
yield systems of switched differential-algebraic equations (swDAEs). Alternating
dynamics of the heart can be well modelled by means of swDAEs. Moreover, to study pulse
wave propagation in arteries and veins, PDE models have been developed. Connection between
the heart and vessels leads to coupling PDEs and swDAEs. This model motivates
to study PDEs coupled with swDAEs, for which the information exchange happens at PDE
boundaries, where swDAE provides boundary conditions to the PDE and PDE outputs serve
as inputs to swDAE. Such coupled systems occur, e.g. while modelling power grids using
telegrapher’s equations with switches, water flow networks with valves and district
heating networks with rapid consumption changes. Solutions of swDAEs might
include jumps, Dirac impulses and their derivatives of arbitrary high orders. As outputs of
swDAE read as boundary conditions of PDE, a rigorous solution framework for PDE must
be developed so that jumps, Dirac impulses and their derivatives are allowed at PDE boundaries
and in PDE solutions. This is a wider solution class than solutions of small bounded
variation (BV), for instance, used in where nonlinear hyperbolic PDEs are coupled with
ODEs. Similarly, in, the solutions to switched linear PDEs with source terms are
restricted to the class of BV. However, in the presence of Dirac impulses and their derivatives,
BV functions cannot handle the coupled systems including DAEs with index greater than one.
Therefore, hyperbolic PDEs coupled with swDAEs with index one will be studied in the BV
setting and with swDAEs whose index is greater than one will be investigated in the distributional
sense. To this end, the 1D space of piecewise-smooth distributions is extended to a 2D
piecewise-smooth distributional solution framework. 2D space of piecewise-smooth distributions
allows trace evaluations at boundaries of the PDE. Moreover, a relationship between
solutions to coupled system and switched delay DAEs is established. The coupling structure
in this thesis forms a rather general framework. In fact, any arbitrary network, where PDEs
are represented by edges and (switched) DAEs by nodes, is covered via this structure. Given
a network, by rescaling spatial domains which modifies the coefficient matrices by a constant,
each PDE can be defined on the same interval which leads to a formulation of a single
PDE whose unknown is made up of the unknowns of each PDE that are stacked over each
other with a block diagonal coefficient matrix. Likewise, every swDAE is reformulated such
that the unknowns are collected above each other and coefficient matrices compose a block
diagonal coefficient matrix so that each node in the network is expressed as a single swDAE.
The results are illustrated by numerical simulations of the power grid and simplified circulatory
system examples. Numerical results for the power grid display the evolution of jumps
and Dirac impulses caused by initial and boundary conditions as a result of instant switches.
On the other hand, the analysis and numerical results for the simplified circulatory system do
not entail a Dirac impulse, for otherwise such an entity would destroy the entire system. Yet
jumps in the flow rate in the numerical results can come about due to opening and closure of
valves, which suits clinical and physiological findings. Regarding physiological parameters,
numerical results obtained in this thesis for the simplified circulatory system agree well with
medical data and findings from literature when compared for the validation
In today’s computer networks we see an ongoing trend towards wireless communication technologies, such as Wireless LAN, Bluetooth, ZigBee and cellular networks. As the electromagnetic spectrum usable for wireless communication is finite and largely allocated for exclusive use by respective license holders, there are only few frequency bands left for general, i.e. unlicensed, use. Subsequently, it becomes apparent, that there will be an overload situation in the unlicensed bands, up to a point where no communication is possible anymore. On the other hand, it has been observed that licensed frequency bands often go unused, at least at some places or over time. Mitola combined both observations and found the term Cognitive Radio Networks [Mit00], denoting a solution for spectrum scarcity. In this concept, so called Secondary Users are allowed to also use licensed bands (attributed to a Primary User) as long as it is vacant.
In such networks, all obligations reside with Secondary Users, especially, they must avoid any interference with the Primary User. They must therefore reliably sense the presence of Primary Users and must decide which available spectrum to use. These two functionalities are called Spectrum Sensing and Spectrum Mobility and describe 2 out of 4 core functionalities of Cognitive Radio Networks and are considered in this thesis.
Regarding Spectrum Sensing, we present our own approach for energy detection in this thesis. Energy detection essentially works by comparing measured energy levels to a threshold. The inherent problem is on how to find such thresholds. Based on existing work we found in literature, we improve techniques and assert the effectiveness of our additions by conducting real world experiments.
Regarding Spectrum Mobility, we concentrate on the point, where the Primary User shows up. At this point, nodes must not use the current channel anymore, i.e. they also have no possibility to agree on another channel to switch to. We solve this problem by employing channel switching, i.e. we change channels proactively, following a schedule shared by all nodes of the network. The main contribution of this thesis is on how to synthesize those schedules to guarantee robust operation under changing conditions. For integration, we considered three dimensions of robustness (of time, of space and of channel) and, based on our algorithms and findings, defined a network protocol, which addresses perturbation within those dimensions. In an evaluation, we showed that the protocol is actually able to maintain robust operation, even if there are large drops in channel quality.
In this dissertation, I will present the studies conducted during my doctoral studies. In spite of a lot of research in the last decades, the complex cognitive processes underlying human memory are not fully unraveled. Furthermore, the development of neuroscientific methods like functional mag-netic resonance imaging (fMRI) and event-related potentials (ERPs) have further build a founda-tion for new insights. Naturally, the utilization of these techniques led to further adaptation of both these techniques and the paradigms in which they have been employed. This can be observed in the research literature on episodic memory retrieval. Familiarity and recollection, have been found to be the chief factors at play during memory retrieval. The two processes have been thoroughly characterized in several studies and reviews (e.g., Mecklinger, 2000; Rugg & Curran, 2007; Yonelinas, 2002; Zimmer & Ecker, 2010), yet there are still open questions that have to be ad-dressed by researchers in this field (c.f., Leynes, Bruett, Krizan, & Veloso, 2017; MacLeod & Donaldson, 2017).
In order to answer these questions, we conducted several studies during my doctoral studies. In Study 1, we developed a paradigm to investigated episodic memory using ERPs. In the study phase, pictorial stimuli were presented which at test were either perceptually identical, perceptually changed, or entirely new. Data collected from a sample of young adults revealed that the paradigm was suitable to elicit ERP correlates of both familiarity and recollection. As the newly developed paradigm yielded similar results as existing literature, we then applied this paradigm in two devel-opmental populations, second-graders and fifth-graders. According to the ERPs, the younger chil-dren seemed to rely on recollection alone, whereas ERPs of older children suggested the use of familiarity for perceptually identical items and only after intentional encoding. In a follow-up study two years later, we used the results from both studies to only slightly refine the paradigm, again administering it to young adults. In this study, Study 3, we found that ERP correlates were much smaller than in the earlier studies, hence we used a data-driven approach to detect time windows of interest. In spite of the large body of research on episodic memory, these studies serve to demon-strate that episodic memory is a complex interplay of several contributing cognitive processes which need to assessed carefully in order to unravel the key factors at play during familiarity and recollection.
Electret filters are electrostatically charged nonwovens which are commonly used in aerosol filtration to remove fine particles from gases. It is known that the charge and thus also the filtration efficiency can degrade over time. Thus, many testing standards require to remove the charge by treatment with liquid isopropanol (IPA) or IPA-saturated air. However, the parameters influencing this discharge have not been completely clarified yet. The aim of this work was, on the one hand, to experimentally investigate the influence of the IPA treatment on different electret filters and, on the other hand, to show the optimization potential of electret filters with respect to efficiency and long-term stability by numerical simulations. The experiments revealed that the air permeability is a central influencing parameter. Small pores lead to a reduced discharge efficiency using liquid IPA, while both treatment methods are suitable for larger pores. The simulations showed that a homogeneous charge distribution within the filter depth is advantageous for the initial performance. In contrast, charge penetrating deeper in the filter medium delays the charge decay and thus increases the operating time, with the trade-off of a lower initial performance
Heading in Soccer: Does Kinematics of the Head‐Neck‐Torso Alignment Influence Head Acceleration?
(2021)
There is little scientific evidence regarding the cumulative effect of purposeful heading. The head-neck-torso alignment is considered to be of great importance when it comes to minimizing potential risks when heading. Therefore, this study determined the relationship between head-neck-torso alignment (cervical spine, head, thoracic spine) and the acceleration of the head, the relationship between head acceleration and maximum ball speed after head impact and differences between head accelerations throughout different heading approaches (standing, jumping, running). A total of 60 male soccer players (18.9 ± 4.0 years, 177.6 ± 14.9 cm, 73.1 ± 8.6 kg) participated in the study. Head accelerations were measured by a telemetric Noraxon DTS 3D Sensor, whereas angles for the head-neck-torso alignment and ball speed were analyzed with a Qualisys Track Manager program. No relationship at all was found for the standing, jumping and running approaches. Concerning the relationship between head acceleration and maximum ball speed after head impact only for the standing header a significant result was calculated (p = 0.024, R2 = .085). A significant difference in head acceleration (p < .001) was identified between standing, jumping and running headers. To sum up, the relationship between head acceleration and head-neck-torso alignment is more complex than initially assumed and could not be proven in this study. Furthermore first data were generated to check whether the acceleration of the head is a predictor for the resulting maximum ball speed after head impact, but further investigations have to follow. Lastly, we confirmed the results that the head acceleration differs with the approach.
Subject of this thesis is the investigation of photo-induced ultrafast elementary processes within the electronic excited-state manifold in mass-selected multinuclear coinage metal complexes (CMCs) in the gas phase. The chief objective is to ascertain how the intramolecular deactivation dynamics and gas phase reactivity are influenced by so-called metallophilic interactions between multiple d^10/d^8 metal centers, which in turn give rise to metal-delocalized electronic transitions. To this end, suitable molecular precursor ions were transferred into the gas phase by electrospray ionization (ESI) and subsequently isolated, activated, and finally analyzed in a Paul-type quadrupole ion trap (QIT) mass spectrometer. The QIT is modified to accept UV/Vis/NIR irradiation from a femtosecond laser setup. By combining several ion trap-based ion activation techniques and electronic photodissociation (PD) spectroscopy, the fragmentation pathways, as well as intrinsic optical properties (electronic PD spectra) of ionic CMCs are explored. In addition, the unconventional time-resolved transient photodissociation (t-PD) method, based on a femtosecond pump-probe excitation scheme, was employed for the first time on CMC ions in isolation, in order to elucidate their intrinsic photodynamics. This thesis mainly comprises five publications, covering the mass spectrometric and laser spectroscopic characterization of multinuclear Ag(I), Au(I), and Pt(II) based ionic complexes.
Multidisciplinary optimizations (MDOs) encompass optimization problems that combine different disciplines into a single optimization with the aim of converging towards a design that simultaneously fulfills multiple criteria. For example, considering both fluid and structural disciplines to obtain a shape that is not only aerodynamically efficient, but also respects structural constraints. Combined with CAD-based parametrizations, the optimization produces an improved, manufacturable shape. For turbomachinery applications, this method has been successfully applied using gradient-free optimization methods such as genetic algorithms, surrogate modeling, and others. While such algorithms can be easily applied without access to the source code, the number of iterations to converge is dependent on the number of design parameters. This results in high computational costs and limited design spaces. A competitive alternative is offered by gradient-based optimization algorithms combined with adjoint methods, where the computational complexity of the gradient calculation is no longer dependent on the number of design parameters, but rather on the number of outputs. Such methods have been extensively used in single-disciplinary aerodynamic optimizations using adjoint fluid solvers and CAD parametrizations. However, CAD-based MDOs leveraging adjoint methods are just beginning to emerge.
This thesis contributes to this field of research by setting up a CAD-based adjoint MDO framework for turbomachinery design using both fluid and structural disciplines. To achieve this, the von Kármán Institute’s existing CAD-based optimization framework cado is augmented by the development of a FEM-based structural solver which has been differentiated using the algorithmic differentiation tool CoDiPack of TU Kaiserslautern. While most of the code could be differentiated in a black-box fashion, special treatment is required for the iterative linear and eigenvalue solvers to ensure accuracy and reduce memory consumption. As a result, the solver has the capability of computing both stress and vibration gradients at a cost independent on the number of design parameters. For the presented application case of a radial turbine optimization, the full gradient calculation has a computational cost of approximately 3.14 times the cost of a primal run and the peak memory usage of approximately 2.76 times that of a primal run.
The FEM code leverages object-oriented design such that the same base structure can be reused for different purposes with minimal re-differentiation. This is demonstrated by considering a composite material test case where the gradients could be easily calculated with respect to an extended design space that includes material properties. Additionally, the structural solver is reused within a CAD-based mesh deformation, which propagates the structural FEM mesh gradients through to the CAD parameters. This closes the link between the CAD shape and FEM mesh. Finally, the MDO framework is applied by optimizing the aerodynamic efficiency of a radial turbine while respecting structural constraints.
In this thesis we study a variant of the quadrature problem for stochastic differential equations (SDEs), namely the approximation of expectations \(\mathrm{E}(f(X))\), where \(X = (X(t))_{t \in [0,1]}\) is the solution of an SDE and \(f \colon C([0,1],\mathbb{R}^r) \to \mathbb{R}\) is a functional, mapping each realization of \(X\) into the real numbers. The distinctive feature in this work is that we consider randomized (Monte Carlo) algorithms with random bits as their only source of randomness, whereas the algorithms commonly studied in the literature are allowed to sample from the uniform distribution on the unit interval, i.e., they do have access to random numbers from \([0,1]\).
By assumption, all further operations like, e.g., arithmetic operations, evaluations of elementary functions, and oracle calls to evaluate \(f\) are considered within the real number model of computation, i.e., they are carried out exactly.
In the following, we provide a detailed description of the quadrature problem, namely we are interested in the approximation of
\begin{align*}
S(f) = \mathrm{E}(f(X))
\end{align*}
for \(X\) being the \(r\)-dimensional solution of an autonomous SDE of the form
\begin{align*}
\mathrm{d}X(t) = a(X(t)) \, \mathrm{d}t + b(X(t)) \, \mathrm{d}W(t), \quad t \in [0,1],
\end{align*}
with deterministic initial value
\begin{align*}
X(0) = x_0 \in \mathbb{R}^r,
\end{align*}
and driven by a \(d\)-dimensional standard Brownian motion \(W\). Furthermore, the drift coefficient \(a \colon \mathbb{R}^r \to \mathbb{R}^r\) and the diffusion coefficient \(b \colon \mathbb{R}^r \to \mathbb{R}^{r \times d}\) are assumed to be globally Lipschitz continuous.
For the function classes
\begin{align*}
F_{\infty} = \bigl\{f \colon C([0,1],\mathbb{R}^r) \to \mathbb{R} \colon |f(x) - f(y)| \leq \|x-y\|_{\sup}\bigr\}
\end{align*}
and
\begin{align*}
F_p = \bigl\{f \colon C([0,1],\mathbb{R}^r) \to \mathbb{R} \colon |f(x) - f(y)| \leq \|x-y\|_{L_p}\bigr\}, \quad 1 \leq p < \infty.
\end{align*}
we have established the following.
\[\]
\(\textit{Theorem 1.}\)
There exists a random bit multilevel Monte Carlo (MLMC) algorithm \(M\) using
\[
L = L(\varepsilon,F) = \begin{cases}\lceil{\log_2(\varepsilon^{-2}}\rceil, &\text{if} \ F = F_p,\\
\lceil{\log_2(\varepsilon^{-2} + \log_2(\log_2(\varepsilon^{-1}))}\rceil, &\text{if} \ F = F_\infty
\end{cases}
\]
and replication numbers
\[
N_\ell = N_\ell(\varepsilon,F) = \begin{cases}
\lceil{(L+1) \cdot 2^{-\ell} \cdot \varepsilon^{-2}}\rceil, & \text{if} \ F = F_p,\\
\lceil{(L+1) \cdot 2^{-\ell} \cdot \max(\ell,1) \cdot \varepsilon^{-2}}\rceil, & \text{if} \ F=f_\infty
\end{cases}
\]
for \(\ell = 0,\ldots,L\), for which exists a positive constant \(c\) such that
\begin{align*}
\mathrm{error}(M,F) = \sup_{f \in F} \bigl(\mathrm{E}(S(f) - M(f))^2\bigr)^{1/2} \leq c \cdot \varepsilon
\end{align*}
and
\begin{align*}
\mathrm{cost}(M,F) = \sup_{f \in F} \mathrm{E}(\mathrm{cost}(M,f)) \leq c \cdot \varepsilon^{-2} \cdot \begin{cases}
(\ln(\varepsilon^{-1}))^2, &\text{if} \ F=F_p,\\
(\ln(\varepsilon^{-1}))^3, &\text{if} \ F=F_\infty
\end{cases}
\end{align*}
for every \(\varepsilon \in {]0,1/2[}\).
\[\]
Hence, in terms of the \(\varepsilon\)-complexity
\begin{align*}
\mathrm{comp}(\varepsilon,F) = \inf\bigl\{\mathrm{cost}(M,F) \colon M \ \text{is a random bit MC algorithm}, \mathrm{error}(M,F) \leq \varepsilon\bigr\}
\end{align*}
we have established the upper bound
\begin{align*}
\mathrm{comp}(\varepsilon,F) \leq c \cdot \varepsilon^{-2} \cdot \begin{cases}
(\ln(\varepsilon^{-1}))^2, &\text{if} \ F=F_p,\\
(\ln(\varepsilon^{-1}))^3, &\text{if} \ F=F_\infty
\end{cases}
\end{align*}
for some positive constant \(c\). That is, we have shown the same weak asymptotic upper bound as in the case of random numbers from \([0,1]\). Hence, in this sense, random bits are almost as powerful as random numbers for our computational problem.
Moreover, we present numerical results for a non-analyzed adaptive random bit MLMC Euler algorithm, in the particular cases of the Brownian motion, the geometric Brownian motion, the Ornstein-Uhlenbeck SDE and the Cox-Ingersoll-Ross SDE. We also provide a numerical comparison to the corresponding adaptive random number MLMC Euler method.
A key challenge in the analysis of the algorithm in Theorem 1 is the approximation of probability distributions by means of random bits. A problem very closely related to the quantization problem, i.e., the optimal approximation of a given probability measure (on a separable Hilbert space) by means of a probability measure with finite support size.
Though we have shown that the random bit approximation of the standard normal distribution is 'harder' than the corresponding quantization problem (lower weak rate of convergence), we have been able to establish the same weak rate of convergence as for the corresponding quantization problem in the case of the distribution of a Brownian bridge on \(L_2([0,1])\), the distribution of the solution of a scalar SDE on \(L_2([0,1])\), and the distribution of a centered Gaussian random element in a separable Hilbert space.
Activity recognition has continued to be a large field in computer science over the last two decades. Research questions from 15 years ago have led to solutions that today support our daily lives. Specifically, the success of smartphones or more recent developments of other smart devices (e.g., smart-watches) is rooted in applications that leverage on activity analysis and location tracking (fitness applications and maps). Today we can track our physical health and fitness and support our physical needs by merely owning (and using) a smart-phone. Still, the quality of our lives does not solely rely on fitness and physical health but also more increasingly on our mental well-being. Since we have learned how practical and easy it is to have a lot of functions, including health support on just one device, it would be specifically helpful if we could also use the smart-phone to support our mental and cognitive health if need be.
The ultimate goal of this work is to use sensor-assisted location and motion analysis to support various aspects of medically valid cognitive assessments.
In this regard, this thesis builds on Hypothesis 3: Sensors in our ubiquitous environment can collect information about our cognitive state, and it is possible to extract that information. In addition, these data can be used to derive complex cognitive states and to predict possible pathological changes in humans. After all, not only is it possible to determine the cognitive state through sensors but also to assist people in difficult situations through these sensors.
Thus, in the first part, this thesis focuses on the detection of mental state and state changes.
The primary purpose is to evaluate possible starting points for sensor systems in order to enable a clinically accurate assessment of mental states. These assessments must work on the condition that a developed system must be able to function within the given limits of a real clinical environment.
Despite the limitations and challenges of real-life deployments, it was possible to develop methods for determining the cognitive state and well-being of the residents. The analysis of the location data provides a correct classification of cognitive state with an average accuracy of 70% to 90%.
Methods to determine the state of bipolar patients provide an accuracy of 70-80\% for the detection of different cognitive states (total seven classes) using single sensors and 76% for merging data from different sensors. Methods for detecting the occurrence of state changes, a highlight of this work, even achieved a precision and recall of 95%.
The comparison of these results with currently used standard methods in psychiatric care even shows a clear advantage of the sensor-based method. The accuracy of the sensor-based analysis is 60% higher than the accuracy of the currently used methods.
The second part of this thesis introduces methods to support people’s actions in stressful situations on the one hand and analyzes the interaction between people during high-pressure activities on the other.
A simple, acceleration based, smartwatch instant feedback application was used to help laypeople to learn to perform CPR (cardiopulmonary resuscitation) in an emergency on the fly.
The evaluation of this application in a study with 43 laypersons showed an instant improvement in the CPR performance of 50%. An investigation of whether training with such an instant feedback device can support improved learning and lead to more permanent effects for gaining skills was able to confirm this theory.
Last but not least, with the main interest shifting from the individual to a group of people at the end of this work, the question: how can we determine the interaction between individuals within a group of people? was answered by developing a methodology to detect un-voiced collaboration in random ad-hoc groups. An evaluation with data retrieved from video footage provides an accuracy of up to more than 95%, and even with artificially introduced errors rates of 20%, still an accuracy of 70% precision, and 90% recall can be achieved.
All scenarios in this thesis address different practical issues of today’s health care. The methods developed are based on real-life datasets and real-world studies.
Biological clocks exist across all life forms and serve to coordinate organismal physiology with periodic environmental changes. The underlying mechanism of these clocks is predominantly based on cellular transcription-translation feedback loops in which clock proteins mediate the periodic expression of numerous genes. However, recent studies point to the existence of a conserved timekeeping mechanism independent of cellular transcription and translation, but based on cellular metabolism. These metabolic clocks were concluded based upon the observation of circadian and ultradian oscillations in the level of hyperoxidized peroxiredoxin proteins. Peroxiredoxins are enzymes found almost ubiquitously throughout life. Originally identified as H2O2 scavengers, recent studies show that peroxiredoxins can transfer oxidation to, and thereby regulate, a wide range of cellular proteins. Thus, it is conceivable that peroxiredoxins, using H2O2 as the primary signaling molecule, have the potential to integrate and coordinate much of cellular physiology and behavior with metabolic changes. Nonetheless, it remained unclear if peroxiredoxins are passive reporters of metabolic clock activity or active determinants of cellular timekeeping. Budding yeast possess an ultradian metabolic clock termed the Yeast Metabolic Cycle (YMC). The most obvious feature of the YMC is a high amplitude oscillation in oxygen consumption. Like circadian clocks, the YMC temporally compartmentalizes cellular processes (e.g. metabolism) and coordinates cellular programs such as gene expression and cell division. The YMC also exhibits oscillations in the level of hyperoxidized peroxiredoxin proteins.
In this study, I used the YMC clock model to investigate the role of peroxiredoxins in cellular timekeeping, as well as the coordination of cell division with the metabolic clock. I observed that cytosolic 2-Cys peroxiredoxins are essential for robust metabolic clock function. I provide direct evidence for oscillations in cytosolic H2O2 levels, as well as cyclical changes in oxidation state of a peroxiredoxin and a model peroxiredoxin target protein during the YMC. I noted two distinct metabolic states during the YMC: low oxygen consumption (LOC) and high oxygen consumption (HOC). I demonstrate that thiol-disulfide oxidation and reduction are necessary for switching between LOC and HOC. Specifically, a thiol reductant promotes switching to HOC, whilst a thiol oxidant prevents switching to HOC, forcing cells to remain in LOC. Transient peroxiredoxin inactivation triggered rapid and premature switching from LOC to HOC. Furthermore, I show that cell division is normally synchronized with the YMC and that deletion of typical 2-Cys peroxiredoxins leads to complete uncoupling of cell division from metabolic cycling. Moreover, metabolic oscillations are crucial for regulating cell cycle entry and exit. Intriguingly, switching to HOC is crucial for initiating cell cycle entry whilst switching to LOC is crucial for cell cycle completion and exit. Consequently, forcing cells to remain in HOC by application of a thiol reductant leads to multiple rounds of cell cycle entry despite failure to complete the preceding cell cycle. On the other hand, forcing cells to remain in LOC by treating with a thiol oxidant prevents initiation of cell cycle entry.
In conclusion, I propose that peroxiredoxins – by controlling metabolic cycles, which are in turn crucial for regulating the progression through cell cycle – play a central role in the coordination of cellular metabolism with cell division. This proposition, thus, positions peroxiredoxins as active players in the cellular timekeeping mechanism.
Diversification is one of the main pillars of investment strategies. The prominent 1/N portfolio, which puts equal weight on each asset is, apart from its simplicity, a method which is hard to outperform in realistic settings, as many studies have shown. However, depending on the number of considered assets, this method can lead to very large portfolios. On the other hand, optimization methods like the mean-variance portfolio suffer from estimation errors, which often destroy the theoretical benefits. We investigate the performance of the equal weight portfolio when using fewer assets. For this we explore different naive portfolios, from selecting the best Sharpe ratio assets to exploiting knowledge about correlation structures using clustering methods. The clustering techniques separate the possible assets into non-overlapping clusters and the assets within a cluster are ordered by their Sharpe ratio. Then the best asset of each portfolio is chosen to be a member of the new portfolio with equal weights, the cluster portfolio. We show that this portfolio inherits the advantages of the 1/N portfolio and can even outperform it empirically. For this we use real data and several simulation models. We prove these findings from a statistical point of view using the framework by DeMiguel, Garlappi and Uppal (2009). Moreover, we show the superiority regarding the Sharpe ratio in a setting, where in each cluster the assets are comonotonic. In addition, we recommend the consideration of a diversification-risk ratio to evaluate the performance of different portfolios.
In an overall effort to contribute to the steadily expanding EO literature, this cumulative dissertation aims to help the literature to advance with greater clarity, comprehensive modeling, and more robust research designs. To achieve this, the first paper of this dissertation focuses on the consistency and coherence in variable choices and modeling considerations by conducting a systematic quantitative review of the EO-performance literature. Drawing on the plethora of previous EO studies, the second paper employs a comprehensive meta-analytic structural equation modeling approach (MASEM) to explore the potential for unique component-level relationships among EO’s three core dimensions in antecedent to outcome relationships. The third paper draws on these component-level insights and performs a finer-grained replication of the seminal MASEM of Rosenbusch, Rauch, and Bausch (2013) that proposes EO as a full mediator between the task environment and firm performance. The fourth and final paper of this cumulative dissertation illustrates exigent endogeneity concerns inherent in observational EO-performance research and provides guidance on how researchers can move towards establishing causal relationships.
Problems, Chances and Limitations of Facilitating Self-Directed Learning at a German Gymnasium
(2020)
Self-directed learning is becoming more important than ever. In a rapidly changing world, learners must be ready to face new obstacles. Self-directed learning gives the learners the chance to adapt to these social contextual changes. But facilitating self-directed learning in formal settings seems to be a risky task and venture. To accomplish its facilitation, many limits must be overcome.
In this thesis, lessons at a German school called a Gymnasium – the type of school where learners can get the highest school level degree – were observed in order to find out in how far elements of self-directed learning can be found in the observed lessons. For the comparison, the process elements of Knowles’ book “Self-Directed Learning: A Guide for Learners and Teachers” from 1975 were adapted to the observations of the lessons.
A central part of the observations and interviews of the teachers was to find out which limitations in the facilitation of self-directed learning can be found in terms of the institutional framework and the attitude of the teachers. The results of the observations highly differentiated. Whereas in many of the observed scientific lessons, many elements of self-directed learning were found, the lessons in social studies were teacher-directed. Also, a different attitude between the teachers was found in terms of the support for self-directed learning.
Importantly, the thesis includes the scientific critic of self-directed learning instead of excluding it and proposes the facilitation of Grow’s “Self-Directed-Learning Model” (1991) where the level of the learner’s self-directed learning is supposed to progress during school. This thesis is relevant for educators, curriculum developers, teachers and policymakers to help them identify the difficulties and chances to facilitate SDL in formal settings.
Although today’s bipeds are capable of demonstrating impressive locomotion skills, in many aspects, there’s still a big gap compared to the capabilities observed in humans. Partially, this is due to the deployed control paradigms that are mostly based on analytical approaches. The analytical nature of those approaches entails strong model dependencies – regarding the robotic platform as well as the environment – which makes them prone to unknown disturbances. Recently, an increasing number of biologically-inspired control approaches have been presented from which a human-like bipedal gait emerges. Although the control structures only rely on proprioceptive sensory information, the smoothness of the motions and the robustness against external disturbances is impressive. Due to the lack of suitable robotic platforms, until today the controllers have been mostly applied to
simulations.
Therefore, as the first step towards a suitable platform, this thesis presents the Compliant Robotic Leg (CARL) that features mono- as well as biarticular actuation. The design is driven by a set of core-requirements that is primarily derived from the biologically-inspired behavior-based bipedal locomotion control (B4LC) and complemented by further functional aspects from biomechanical research. Throughout the design process, CARL is understood as a unified dynamic system that emerges from the interplay of the mechanics, the electronics, and the control. Thus, having an explicit control approach and the respective gait in mind, the influence of each subsystem on the characteristics of the overall system is considered
carefully.
The result is a planar robotic leg whose three joints are driven by five highly integrated linear SEAs– three mono- and two biarticular actuators – with minimized reflected inertia. The SEAs are encapsulated by FPGA-based embedded nodes that are designed to meet the hard application requirements while enabling the deployment of a full-featured robotic framework. CARL’s foot is implemented using a COTS prosthetic foot; the sensor information is obtained from the deformation of its main structure. Both subsystems are integrated into a leg structure that matches the proportions of a human with a size of 1.7 m.
The functionality of the subsystems, as well as the overall system, is validated experimentally. In particular, the final experiment demonstrates a coordinated walking motion and thereby confirms that CARL can produce the desired behavior – a natural looking, human-like gait is emerging from the interplay of the behavior-based walking control and the mechatronic system. CARL is robust regarding impacts, the redundant actuation system can render the desired joint torques/impedances, and the foot system supports the walking structurally while it provides the necessary sensory information. Considering that there is no movement of the upper trunk, the angle and torque profiles are comparable to the ones found in humans.
With the technological advancement in the field of robotics, it is now quite practical to acknowledge the actuality of social robots being a part of human's daily life in the next decades. Concerning HRI, the basic expectations from a social robot are to perceive words, emotions, and behaviours, in order to draw several conclusions and adapt its behaviour to realize natural HRI. Henceforth, assessment of human personality traits is essential to bring a sense of appeal and acceptance towards the robot during interaction.
Knowledge of human personality is highly relevant as far as natural and efficient HRI is concerned. The idea is taken from human behaviourism, with humans behaving differently based on the personality trait of the communicating partners. This thesis contributes to the development of personality trait assessment system for intelligent human-robot interaction.
The personality trait assessment system is organized in three separate levels. The first level, known as perceptual level, is responsible for enabling the robot to perceive, recognize and understand human actions in the surrounding environment in order to make sense of the situation. Using psychological concepts and theories, several percepts have been extracted. A study has been conducted to validate the significance of these percepts towards personality traits.
The second level, known as affective level, helps the robot to connect the knowledge acquired in the first level to make higher order evaluations such as assessment of human personality traits. The affective system of the robot is responsible for analysing human personality traits. To the best of our knowledge, this thesis is the first work in the field of human-robot interaction that presents an automatic assessment of human personality traits in real-time using visual information. Using psychology and cognitive studies, many theories has been studied. Two theories have been been used to build the personality trait assessment system: Big Five personality traits assessment and temperament framework for personality traits assessment.
By using the information from the perceptual and affective level, the last level, known as behavioural level, enables the robot to synthesize an appropriate behaviour adapted to human personality traits. Multiple experiments have been conducted with different scenarios. It has been shown that the robot, ROBIN, assesses personality traits correctly during interaction and uses the similarity-attraction principle to behave with similar personality type. For example, if the person is found out to be extrovert, the robot also behaves like an extrovert. However, it also uses the complementary attraction theory to adapt its behaviour and complement the personality of the interaction partner. For example, if the person is found out to be self-centred, the robot behaves like an agreeable in order to flourish human-robot interaction.