This dissertation explores how entrepreneurs develop their employees to qualify them for their tasks in entrepreneurial firms, and analyzes in what way effectuation and entrepreneurial passion determine how entrepreneurs influence their employees.
In current practices of system-on-chip (SoC) design a trend can be observed to integrate more and more low-level software components into the system hardware at different levels of granularity. The implementation of important control functions and communication structures is frequently shifted from the SoC’s hardware into its firmware. As a result, the tight coupling of hardware and software at a low level of granularity raises substantial verification challenges since the conventional practice of verifying hardware and software independently is no longer sufficient. This calls for new methods for verification based on a joint analysis of hardware and software.
This thesis proposes hardware-dependent models of low-level software for performing formal verification. The proposed models are conceived to represent the software integrated with its hardware environment according to the current SoC design practices. Two hardware/software integration scenarios are addressed in this thesis, namely, speed-independent communication of the processor with its hardware periphery and cycle-accurate integration of firmware into an SoC module. For speed-independent hardware/software integration an approach for equivalence checking of hardware-dependent software is proposed and an evaluated. For the case of cycle-accurate hardware/software integration, a model for hardware/software co-verification has been developed and experimentally evaluated by applying it to property checking.
The main goal of this work was the study of the applicability of a polymer film heat exchanger concept for the applications in the chemical industry, such as the condensation of organic solvents. The polymer film heat exchanger investigated is a plate heat exchanger with very thin (0.025 – 0.1 mm) plates or films, which separate the fluids and enable the heat transfer. After a successful application of this concept to seawater desalination in a previous work, a further step is in chemical engineering, where the good chemical resistance of polymers in aggressive fluids is the challenge.
Two approaches were performed in this work. The first one was experimental and included the study of the chemical and mechanical resistance of preselected films, made of polymer materials, such as polyimide (PI), polyethylene terephthalate (PET) and polytetrafluoroethylene (PTFE). To simulate realistic operating conditions in a heat exchanger the films were exposed to a combined thermal (up to 90°C) and mechanical pressure loads (4-6 bar) with permanent contact with the relevant organic solvents, such as toluene, hexane, heptane and tetrahydrofuran (THF). Furthermore, a lab-scale apparatus and a full-scale demonstrator were manufactured in cooperation with two industrial partners. These were used for the investigation of the heat transfer performance for operating modes with and without phase change.
In addition to the experimental work, a coupled finite element –computational fluid dynamics (FEM-CFD)-model was developed, based on the fluid-structure-interaction (FSI). Two major tasks had to be solved here. The first one was the modelling of the condensation process, based on available mathematical models and energy balances. The second one was the consideration of the partially reversible deformation of the used film during operation. Since this deformation changes the geometry of the fluid channels also has an influence on the overall performance of the apparatus, a coupled FEM-CFD model was developed.
During the experimental study of the chemical resistance of the films, the PTFE film showed the best performance, and hence can be used for all four tested solvents. For the polyimide film, failures while exposed to THF were observed, and the PET film can only be used with water and hexane. With the used lab-scale heat exchanger and the full-scale demonstrator competitive overall heat transfer coefficients between 270 W/m²K and 700 W/m²K could be reached for the liquid-liquid (water-water, water-hexane) operation mode without phase change. For the condensation process, overall heat transfer coefficients of up to 1700/m²K could be obtained.
The numerical approach led to a well-functioning coupled model in a very small scale (1 cm²). An upscale, however, failed due to enormous hardware resources necessary required for the simulation of the entire full-scale demonstrator. The main reason for this is the very low thickness of the films, which leads to tiny mesh element sizes (<0.05 mm) necessary to model the deformation of the film. The modelling of the liquid-liquid heat transfer provided an acceptable accuracy (approx. 10%), but at very low rates the deviations were then higher (over 30%). The results of the condensation modelling were ambivalent. One the one hand a physically plausible model was developed, which could map the entire condensation process. On the other hand, the corresponding energy balance revealed major inaccuracy and hence could not be used for the determination of the overall heat transfer and showed the current limits of the FEM-CFD approach.
This dissertation describes an indoor localization system based on oscillating magnetic fields and the underlying processing architecture. The system consists of several fixed anchor points, generating the magnetic fields (transmitter), and wearable magnetic field measurement units, whose position should be determined (receiver). The system is evaluated in different environments and application areas. Additionally, various fields of application are discussed and assessed in ubiquitous and pervasive computing and Ambient Assisted Living. The fusion of magnetic field-based distance information and positions derived from LIDAR distance measurements is described and evaluated.
The system architecture consists of three layers, a physical layer, a layer for position and distance estimation between a magnetic field transmitter and a receiver, and a layer which uses several measurements to different transmitters to estimate the overall position of a wearable measurement unit.
Each layer covers different aspects which have to be taken care of when magnetic field information is processed. Especially the properties of the generated magnetic field information are considered in the processing algorithms.
The physical layer covers the magnetic field generation and magnetic Field-Based information transfer, synchronization of a transmitter and the receivers and the description of the locally measured magnetic fields on the receiver side. After a transfer of this information to a central processing unit, the hardware specific signal levels are transformed to the levels of the theoretical magnetic field models. The values are then used to estimate candidate positions and distances. Due to symmetrical effects of the magnetic fields, it is only possible to reduce the receiver position to 8 points around the transmitter (one position in each of the octants of the coordinate system). The determined positions have a mean error of 108 cm, the average error of the distance is 40 cm.
On top of this, the distance and position information against different transmitters are fused, this covers clock synchronization of transmitters, triggering and scheduling sequences and distance and position based localization and tracking algorithms. The magnetic-field-based indoor localization system has been evaluated in different applications and environments; the mean position error is 60 cm to 70 cm depending on the environment. A comparison against an RF-based indoor localization system shows the robustness of magnetic fields against RF shadows caused by big metal objects.
We additionally present algorithms for regions of interest detection, working on raw magnetic field information and transformed position and distance information. Setups in larger areas can distinguish regions which are further than 50 cm apart, small scale coil setups (3 transmitters in 2m^3) allow to resolve regions below 20 cm.
In the end, we describe a fusion algorithm for a wearable localization system based on 4 LIDAR distance measurement units and magnetic field-based distance estimation. The magnetic field indoor localization system provides distance proximity information which is used to resolve ambiguous position estimates of the LIDAR system. In a room (8m × 10m), we achieve a mean error of 8 cm.
Advanced sensing systems, sophisticated algorithms, and increasing computational resources continuously enhance the advanced driver assistance systems (ADAS). To date, despite that some vehicle based approaches to driver fatigue/drowsiness detection have been realized and deployed, objectively and reliably detecting the fatigue/drowsiness state of driver without compromising driving experience still remains challenging. In general, the choice of input sensorial information is limited in the state-of-the-art work. On the other hand, smart and safe driving, as representative future trends in the automotive industry worldwide, increasingly demands the new dimensional human-vehicle interactions, as well as the associated behavioral and bioinformatical data perception of driver. Thus, the goal of this research work is to investigate the employment of general and custom 3D-CMOS sensing concepts for the driver status monitoring, and to explore the improvement by merging/fusing this information with other salient customized information sources for gaining robustness/reliability. This thesis presents an effective multi-sensor approach with novel features to driver status monitoring and intention prediction aimed at drowsiness detection based on a multi-sensor intelligent assistance system -- DeCaDrive, which is implemented on an integrated soft-computing system with multi-sensing interfaces in a simulated driving environment. Utilizing active illumination, the IR depth camera of the realized system can provide rich facial and body features in 3D in a non-intrusive manner. In addition, steering angle sensor, pulse rate sensor, and embedded impedance spectroscopy sensor are incorporated to aid in the detection/prediction of driver's state and intention. A holistic design methodology for ADAS encompassing both driver- and vehicle-based approaches to driver assistance is discussed in the thesis as well. Multi-sensor data fusion and hierarchical SVM techniques are used in DeCaDrive to facilitate the classification of driver drowsiness levels based on which a warning can be issued in order to prevent possible traffic accidents. The realized DeCaDrive system achieves up to 99.66% classification accuracy on the defined drowsiness levels, and exhibits promising features such as head/eye tracking, blink detection, gaze estimation that can be utilized in human-vehicle interactions. However, the driver's state of "microsleep" can hardly be reflected in the sensor features of the implemented system. General improvements on the sensitivity of sensory components and on the system computation power are required to address this issue. Possible new features and development considerations for DeCaDrive are discussed as well in the thesis aiming to gain market acceptance in the future.
Redox-neutral decarboxylative coupling reactions have emerged as a powerful strategy for C-C bond formation. However, the existing reaction conditions possess limitations, such as the coupling of aryl halides restricted to ortho-substituted benzoic acids; alkenyl halides were not applicable in decarboxylative coupling reaction. Within this thesis, the developments of Pd/Cu bimetallic catalyst systems are presented to overcome the limitations.
In the first part of the PhD work, a customized bimetallic PdII/CuI catalyst system was successfully developed to facilitate the decarboxylative cross-coupling of non-ortho-substituted aromatic carboxylates with aryl chlorides. The restriction of decarboxylative cross-coupling reactions to ortho-substituted or heterocyclic carboxylate substrates was overcome by holistic optimization of this bimetallic Cu/Pd catalyst system. All kinds of benzoic acids regardless of their substitution pattern now can be applied in decarboxylative cross-coupling reaction. This confirms prediction by DFT studies that the previously observed limitation to certain activated carboxylates is not intrinsic. The catalyst system also presents higher performance in the coupling of ortho-substituted benzoates, giving much higher yields than those previously reported. ortho-Methyl benzoate and ortho-phenyl benzoate which have never before been converted in decarboxylative coupling reactions, gave reasonable yields. These together further confirm the superiority of the new protocol.
In the second part of the PhD work, arylalkenes syntheses via two different Pd/Cu bimetallic-catalyzed decarboxylative couplings have been developed. This part consists of two projects: 2a) decarboxylative coupling of alkenyl halides; 2b) decarboxylative Mizoroki-Heck coupling of aryl halides with α,β-unsaturated carboxylic acids.
In project 2a, widely available, inexpensive, bench-stable aromatic carboxylic acids are used as nucleophile precursors instead of expensive and sensitive organometallic reagents that are commonly used in previously reported transition-metal catalyzed cross-couplings of alkenyl halides. With this protocol, alkenyl halides for the first time are used in decarboxylative coupling reaction, allowing regiospecific synthesis of a broad range of (hetero)arylalkenes in high yields. Unwanted double bond isomerization, a common side reaction in the alternative Heck reactions especially in the coupling of cycloalkenes or aliphatic alkenes, did not take place in this decarboxylative coupling reaction. Polysubstituted alkenes that hard to access with Heck reaction are also produced in good yields. The reaction can easily be scaled up to gram scale. The synthetic utility of this reaction was also demonstrated by synthesizing an important intermediate of fungicidal compound in high yield within 2 steps.
In project 2b, a Cu/Pd bimetallic catalyzed decarboxylative Mizoroki-Heck coupling of aryl halides with α, β-unsaturated carboxylic acids was successfully developed in which the carboxylate group directs the arylation into its β-position before being tracelessly removed via protodecarboxylation. It opens up a convenient synthesis of unsymmetrical 1,1-disubstituted alkenes from widely available precursors. This reaction features good regioselectivity, which is complementary to that of traditional Heck reactions, and also presents excellent functional group tolerance. Moreover, a one-pot 3-step 1,1-diarylethylene synthesis from methyl acrylate was achieved, where solvent changes or isolation of intermediates are not required. This subproject presents an example of carboxylic acids utility in synthesizing valuable compounds which are hard to access via conventional methodologies.
Rigidness of the Internet causes its architectural design issues such as interdependencies among the layers, no cross-layer information exchange, and applications dependency on the underlying protocols implementation.
G-Lab (i.e., http://www.german-lab.de/) is a research project for Future Internet Architecture (FIA), which focuses on problems of the Internet such as rigidness, mobility, and addressing. Where the focus of ICSY (i.e., www.icsy) was on providing the flexibility in future network architectures. An approach so-called Service Oriented Network Architecture (SONATE) is proposed to compose the protocols dynamically. SONATE is based on principles of the service-oriented architecture (SOA), where protocols are decomposed in software modules and later they are put together on demand to provide the desired service.
This composition of functionalities can be performed at various time-epochs (e.g., run-time, design-time, deployment-time). However, these epochs have trade-off in terms of the time-complexity (i.e., required setup time) and the provided flexibility. The design-time is the least time critical in comparison to other time phases, which makes it possible to utilize human-analytical capability. However, the design-time lacks the real-time knowledge of requirements and network conditions, what results in inflexible protocol graphs, and they cannot be changed at later stages on changing requirements. Contrary to the design-time, the run-time is most time critical where an application is waiting for a connection to be established, but at the same time it has maximum information to generate a protocol graph suitable to the given requirements.
Considering limitations above of different time-phases, in this thesis, a novel intermediate functional composition approach (i.e., Template-Based Composition) has been presented to generate requirements aware protocol graphs. The template-based composition splits the composition process across different time-phases to exploit the less time critical nature and human-analytical availability of the design-time, ability to instantaneously deploy new functionalities of the deployment time and maximum information availability of the run-time. The approach is successfully implemented , demonstrated and evaluated based on its performance to know the implications for the practical use.
When designing autonomous mobile robotic systems, there usually is a trade-off between the three opposing goals of safety, low-cost and performance.
If one of these design goals is approached further, it usually leads to a recession of one or even both of the other goals.
If for example the performance of a mobile robot is increased by making use of higher vehicle speeds, then the safety of the system is usually decreased, as, under the same circumstances, faster robots are often also more dangerous robots.
This decrease of safety can be mitigated by installing better sensors on the robot, which ensure the safety of the system, even at high speeds.
However, this solution is accompanied by an increase of system cost.
In parallel to mobile robotics, there is a growing amount of ambient and aware technology installations in today's environments - no matter whether in private homes, offices or factory environments.
Part of this technology are sensors that are suitable to assess the state of an environment.
For example, motion detectors that are used to automate lighting can be used to detect the presence of people.
This work constitutes a meeting point between the two fields of robotics and aware environment research.
It shows how data from aware environments can be used to approach the abovementioned goal of establishing safe, performant and additionally low-cost robotic systems.
Sensor data from aware technology, which is often unreliable due to its low-cost nature, is fed to probabilistic methods for estimating the environment's state.
Together with models, these methods cope with the uncertainty and unreliability associated with the sensor data, gathered from an aware environment.
The estimated state includes positions of people in the environment and is used as an input to the local and global path planners of a mobile robot, enabling safe, cost-efficient and performant mobile robot navigation during local obstacle avoidance as well as on a global scale, when planning paths between different locations.
The probabilistic algorithms enable graceful degradation of the whole system.
Even if, in the extreme case, all aware technology fails, the robots will continue to operate, by sacrificing performance while maintaining safety.
All the presented methods of this work have been validated using simulation experiments as well as using experiments with real hardware.
Synapses play a central role in the information propagation in the nervous system. A better understanding of synaptic structures and processes is vital for advancing nervous disease research. This work is part of an interdisciplinary project that aims at the quantitative examination of components of the neuromuscular junction, a synaptic connection between a neuron and a muscle cell.
The research project is based on image stacks picturing neuromuscular junctions captured by modern electron microscopes, which permit the rapid acquisition of huge amounts of image data at a high level of detail. The large amount and sheer size of such microscopic data makes a direct visual examination infeasible, though.
This thesis presents novel problem-oriented interactive visualization techniques that support the segmentation and examination of neuromuscular junctions.
First, I introduce a structured data model for segmented surfaces of neuromuscular junctions to enable the computational analysis of their properties. However, surface segmentation of neuromuscular junctions is a very challenging task due to the extremely intricate character of the objects of interest. Hence, such problematic segmentations are often performed manually by non-experts and thus requires further inspection.
With NeuroMap, I develop a novel framework to support proofreading and correction of three-dimensional surface segmentations. To provide a clear overview and to ease navigation within the data, I propose the surface map, an abstracted two-dimensional representation using key features of the surface as landmarks. These visualizations are augmented with information about automated segmentation error estimates. The framework provides intuitive and interactive data correction mechanisms, which in turn permit the expeditious creation of high-quality segmentations.
While analyzing such segmented synapse data, the formulation of specific research questions is often impossible due to missing insight into the data. I address this problem by designing a generic parameter space for segmented structures from biological image data. Furthermore, I introduce a graphical interface to aid its exploration, combining both parameter selection as well as data representation.