Browsing by Type "Doctoral Thesis"

Since we are living in a three-dimensional world, an adequate description of our environment for many applications includes the relative position and motion of the different objects in a scene. Nature has satisfied this need for spatial perception by providing most animals with at least two eyes. This stereo vision ability is the basis that allows the brain to calculate qualitative depth information of the observed scene. Another important parameter in the complex human depth perception is our experience and memory. Although it is far more difficult, a human being is even able to recognize depth information without stereo vision. For example, we can qualitatively deduce the 3D scene from most photos, assuming that the photos contain known objects [COR]. The acquisition, storage, processing and comparison of such a huge amount of information requires enormous computational power - with which nature fortunately provides us. Therefore, for a technical implementation, one should resort to other simpler measurement principles. Additionally, the qualitative distance estimates of such knowledge-based passive vision systems can be replaced by accurate range measurements. Imaging 3D measurement with useful distance resolution has mainly been realized so far with triangulation systems, either passive triangulation (stereo vision) or active triangulation (e.g. projected fringe methods). These triangulation systems have to deal with shadowing effects and ambiguity problems (projected fringe), which often restrict the range of application areas. Moreover, stereo vision cannot be used to measure a contrastless scene. This is because the basic principle of stereo vision is the extraction of characteristic contrast-related features within the observed scene and the comparison of their position within the two images. Also, extracting the 3D information from the measured data requires an enormous time-consuming computational effort. High resolution can only be achieved with a relatively large triangulation base and hence large camera systems. A smarter range measurement method is the TOF ( T ime- O f- F light) principle, an optical analogy to a bat´s ultrasonic system rather than human´s stereo vision. So far TOF systems are only available as 1D systems (point measurement), requiring laser scanners to acquire 3D images. Such TOF scanners are expensive, bulky, slow, vibration sensitive and therefore only suited for restricted application fields. In this dissertation an imaging, i.e. non-scanning TOF-camera is introduced, based on an array of demodulation pixels, where each pixel can measure both the background intensity and the individual arrival time of an RF-modulated (20 MHz) scene illumination with an accuracy of a few hundreds of picoseconds (300⋅10 -12 s). The pixel´s working concept is based on the CCD principle ( C harge C oupled D evice), allowing the transportation, storage and accumulation of optically generated charge carriers to defined local sites within the imaging device. This process is extremely fast and essentially loss-free. We call our new, powerful high-functionality pixels demodulation pixels because they extract the target´s distance and reflectivity from the received optical signal. This extracted information is modulated into the active optical signal during the time of propagation of the light (or time of flight) through the observed scene. Each pixel works like an individual high-precision stopwatch, and since its realization is mainly based on CMOS technology this new technique will benefit from the ongoing technology developments in terms of improved time- and hence distance resolution. Thanks to the use of CMOS, all commonly known CMOS APS ( A ctive P ixel S ensor) features ( R egions O f I nterest addressing: ROI, AD conversion, etc.) can be implemented monolithically in the future. The imaging devices have been fabricated in a 2 µm CMOS/CCD process, a slightly modified CMOS process which is available as an inexpensive prototyping service ( M ulti P roject W afer: MPW). This process offers the freedom to implement CCDs with sufficiently good performance for our application, although the performance is inferior to dedicated CCD technologies. We have realized and characterized several different pixel structures and will present these results here. The demodulation pixel with the best fill-factor and demodulation performance has been implemented (1) as a line sensor with 108 pixels and (2) as an image sensor with 64 x 25 pixels. Both devices have been integrated in separate range cameras working with modulated LED illumination and covering a distance range of 7.5 up to 15 meters. For non-cooperative diffusely reflecting targets these cameras achieve centimeter accuracy. With the single exception of the demodulation pixel array itself, only standard electronic and optical components have been used in these range cameras. For a resolution of 5 centimeters, an optical power of 600 fW per pixel is sufficient, assuming an integration time of 50 ms (20 Hz frame rate of 3D images). This low optical power implies that only 0.06 electrons are generated per modulation period (T mod =50 ns at 20 MHz modulation frequency). Furthermore, we present an in-depth analysis of the influences of non-linearities in the electronics, aliasing effects, integration time and modulation functions. Also, an optical power budget and a prediction for the range accuracy is derived as a function of the ratio of active illumination to background illumination. The validity of this equation is confirmed by both computer simulations and experimental measurements with real devices. Thus, we are able to predict the range accuracy for given integration time, optical power, target distance and reflectance. With this work we demonstrate the first successful realization of an all-solid-state 3D TOF range-camera without moving parts that is based on a dedicated customized PhotoASIC. The measured performance is very close to the theoretical limits. We clearly demonstrate that optical 3D-TOF is an excellent, cost-effective tool for all modern vision problems, where the relative position or motion of objects need to be monitored.

The major part of this thesis deals with 6 Li solid state spectroscopic investigations of ternary and quaternary lithium magnesium chlorides. The 6 Li MAS-NMR spectres show two separate signals in accordance with the two different sites of the Li ions in an inverse spinel structure. Due to comparative 6 Li MAS-NMR spectroscopic measurements of 6 Li 2 ZnCl 4 (Li occupies only the octahedral 16d sites) and of the lithium deficient compounds Li 2-2x Mg 1+x Cl 4 , Li 2-x Cu x MgCl 4 and Li 2-x Na x MgCl 4 the signal 1 with a chemical shift of 1.2 ppm can be assigned to the tetrahedral co-ordinated 8a site and signal 2 with a chemical shift of 0.3 ppm to the octahedral co-ordinated 16d site in an inverse spinel type. 6 Li MAS NMR spectra including 1D-EXSY experiments have been recorded and are discussed with respect to the dynamics of the tetrahedral co-ordinated lithium ions in Li 2 MgCl 4 and the activation energy could be determined to 6.6 kJ/mol. This can be ascribed to a local motion of the Li ions within a tetrahedral site. Neutron diffraction experiments of Co(IO 3 ) 2 ⋅4H 2 O single crystals are carry out in order to allow a more detailed interpretation of IR- and Raman-data. This exhibits that the interaction of the layered structure is not caused by hydrogen bonds but by interionic I-O-interactions with a I-O(1) distance of 277.9(1) ppm. Furthermore the structures of Li 1,25 Cd 1,67 In 0,48 Cl 6 , Li 0,24 Mn 1,71 In 0,78 Cl 6 , (NH 4 ) 21 [H 3 Mo 51 (MoNO) 6 V 6 O 183 (H 2 O) 18 ]⋅53H 2 O, Cd 0,967 Ga 0,022 Cr 2 Se 4 und Pd(S 2 CN(C 5 H 11 ) 2 ) 2 could be determined by both X-ray and neutron-diffraction experiments.

This study investigated accessibility to inclusive education for children with disabilities in two selected districts in Ghana (Ga East and New Juabeng respectively). A total of two hundred and eighteen respondents were involved and the study employed mixed methods, that is combination of both quantitative and qualitative methods were relied on and simple random and purposive samplings techniques were used in selecting participants. Analysis of data showed evidence of acceptance of children with disabilities into the mainstream schools but there are factors that posed challenges for complete practice of inclusive education. These factors include stigmatisation, discrimination and cultural beliefs, teacher’s competence and attitudes, parental involvement, unavailability of resources and inadequate policies. These factors were found to be barriers that influence accessibility to education for children with disabilities. Discussions of the study attempted to demonstrate children with disabilities get access to inclusive education as a result of general education policy such as FCUBE policy, but nevertheless there are challenges. As a result of these challenges children with disabilities are not benefit from education. Understanding and following the discussions it was concluded that the factors identified in the study as barriers to accessibility to education for children with disabilities need to be addressed for successful inclusive education practice.

Tribology represents a research field which has been extensively explored for a long time but a little fundamental understanding of various observations has been achieved. The main reason for this lies in the enormous complexity of the phenomena acting on the forces between two contacting bodies which are moved with respect to each other. However, the understanding of the central role of tribology in the modern society in the context of optimization of the performance as well as the lifetime of many products demands dedicated research in this interdisciplinary field. Today the technological progress in the scanning probe techniques opens up the potential to study contact phenomena on the single asperity level. In this thesis work, the influence of surface roughness, mechanical properties, adhesion force, and external parameters (applying normal load, scratching speed, and loading rate) on friction are identified. Adhesion force between silica microspheres of different sizes and different rough surfaces (silicon and diamond-like carbon (DLC)) is measured using atomic force microscopy (AFM). The surface roughness, asperity geometry, and size of adhering particles play an important role in determining the adhesion force. Adhesion force between adhering particle and smooth surface linearly increases with size of the adhering particle. On increasing surface roughness, the adhesion force is found to show decreasing trend initially, followed by an increasing trend. The results are compared with existing as well as proposed models. The influence of applied normal load on the tribological behavior between spherical probe and various rough surfaces such as fused silica, aluminum, DLCs, and Si-C-B-N-O coatings, is experimentally investigated using Nanoindenter and AFM. At a sufficient low level of applied normal load, wherein the contact is elastic, the friction coefficient decreases with load. At higher load, the contact involves the plastic deformation and friction coefficient will be constant. At very high load, friction coefficient increases with applied load. The surface roughness and mechanical properties (hardness and elastic modulus) have significant influence on the friction as they determine the degree of plastic deformation. An additional lateral force due to the intrinsic adhesive force is seen. After eliminating this additional adhesive force term, at a sufficient low level of applied normal load, wherein the contact is elastic, the friction coefficient is constant. By eliminating the adhesion component from friction, at increased normal loads the contact involves plastic deformation and the friction coefficient increases with increasing normal load. The friction coefficient increases on decreasing the loading rate and increasing the scratching speed. The critical load range for a transition from either predominantly elastic to elastic-plastic contact or elastic-plastic to predominantly plastic contact between the indenter and sample increases with increasing the size of tip and the scratching speed, and it decreases with surface roughness and loading rate. The results are compared with existing models.

The global trends in the construction of modern structures require the integration of sensors together with data recording and analysis modules so that its integrity can be continuously monitored for safe-life, economic and ecological reasons. This process of measuring and analysing the data from a distributed sensor network all over a structural system in order to quantify its condition is known as structural health monitoring (SHM). The research presented in this thesis is motivated by the need to improve the inspection capabilities and reliability of SHM systems based on ultrasonic guided waves with focus on the acoustic emission and acousto-ultrasonics techniques. The use of a guided wave-based approach is driven by the fact that these waves are able to propagate over relatively long distances, interact sensitively with and/or being related to different types of defect. The main emphasis of the thesis is concentrated on the development of different methodologies based on signal analysis together with the fundamental understanding of wave propagation for the solution of problems such as damage detection, localisation and identification. The behaviour of guided waves for both techniques is predicted through modelling in order to investigate the characteristics of the modes being propagated throughout the evaluated structures and support signal analysis. The validity of the developed model is extensively investigated by contrasting numerical simulations and experiments. In this thesis special attention is paid to the development of efficient SHM methodologies. This fact requires robust signal processing techniques for the correct interpretation of the complex ultrasonic waves. Therefore, a variety of existing algorithms for signal processing and pattern recognition are evaluated and integrated into the different proposed methodologies. Additionally, effects such as temperature variability and operational conditions are experimentally studied in order to analyse their influence on the performance of developed methodologies. At the end, the efficiency of these methodologies are experimentally evaluated in diverse isotropic and anisotropic composite structures.

Efficient noise control is an important and crucial issue in a wide range of engineering applications. Porous materials with dispersed micro-pores are commonly used due to their high capacity to absorb acoustic wave energy and mitigate undesirable noises. This thesis aims to improve the low-frequency sound absorption performance in a broad frequency range. For this purpose, two porous metamaterial (PM) structures are proposed, namely, the slit-perforated multi-layered porous metamaterial (SMPM) structure and the novel multiscale porous metamaterial (MPM) structure. The SMPM structure consists of periodic porous matrix layers and second-type porous layers with periodically distributed slits, while the novel MPM structure consists of a porous matrix with periodically distributed meso-pores, in which a second porous layer is introduced as an interlayer between the matrix and the meso-pores. Theoretical models based on the homogenization schemes and semi-phenomenological approaches to describe the macroscopic dynamic properties of the porous materials are adopted, while numerical methods based on the transfer matrix method (TMM) and the finite element method (FEM) are applied to compute the acoustic wave absorption and mitigation characteristics of the proposed PM structures in both room-temperature and high-temperature environments. In particular, the band structures or dispersion curves especially the frequency bandgaps, and the acoustic wave absorption coefficients are analyzed and discussed in details. The research findings and the knowledge gained in this thesis may provide a deep insight into the acoustic wave absorption and mitigation characteristics and the corresponding physical mechanisms in porous metamaterial structures, which are highly valuable for the design, optimization, realization and application of novel porous metamaterial structures

Software development is a complex and demanding task, frequently carried out by teams of multiple developers. Software development methods define the steps to be taken and the products to be maintained in order to attain a successful project outcome. Thus, methods outline the structure of a project. In the early phases, upper-CASE tools are used to edit, check, and transform various types of software documents. The requirements for these tools vary considerably, depending on the organization, user role, task, and kind of system to be developed. Consequently, tools have to be adaptable to the actual situation. Traditional CASE tools do not fulfill this demand sufficiently. Meta environments support tool developers in building customized tools. However, known systems are focused on only one aspect: The adaptation to different document types or the adaptation to different process models. The thesis describes an approach for building process-centered software development environments (PSEEs). The resulting environments contain tools which are tailored to the given situation and are integrated with the software development process. An important component of these environments is an Object Management System (OMS). It serves as a central repository for both, software documents and information concerning the current process state. The OMS integrates the various tools with their different views on the common data- base and offers numerous services which are used for implementing tool functions - among them views, access controls, transactions, and distributed notifications. Thereby, the costs for building meta environments and for building their instances, i.e. concrete environments, are reduced. The services mentioned can only be used if data models are fine-grained and if tools implement an OMS-oriented architecture. In the thesis, this architecture has been implemented in a framework. It is used to build distributed multi-user tools. The framework consists of components for building CASE tools and process tools. The configuration of tools depends on the data model of software documents and on additional information. These additional information are codified in tool parameters which are associated to type definitions in the data model. The resulting tool specification is called tool schema. Besides this black-box reuse, tool components can be extended with tool-specific functionality. This white-box reuse requires a more extensive knowledge and offers more flexible means for tool adaptation. For the description of process models we define a simple process modeling language which is used for demonstration purposes only. Based on the framework, a process engine can be built. It controls process performance and can be flexibly extended with process-specific functionality. CASE tools adapt themselves to the current process situation and allow their users to influence process performance. Additionally, tools for planning and managing software processes have been built and have been integrated into the environment to underline the flexibility of the approach.

Real-time computing systems are designed to meet strict timing constraints and respond to events or inputs within specified deadlines. These systems are commonly used in safety-critical applications such as spacecraft, medical devices, industrial control, and automotive systems. Engineers rely on various scheduling techniques to ensure that timing constraints are met. One such technique is static resource allocation in time-triggered systems. Static resource allocation offers valuable advantages in terms of system dependability by minimizing message congestion and contention, enabling efficient resource usage in network-on-chip (NoC) architectures. This is achieved through the pre-allocation of resources and scheduling of tasks, resulting in improved system throughput and reduced jitter. The time-triggered concept in NoC architectures provides precise knowledge about the permitted points in time for message exchanges between cores, serving as a fundamental building block for fault containment, real-time support, and enhanced system performance. While static resource allocation excels in minimizing congestion and contention and contributes to system dependability, it may pose challenges in accommodating dynamic workloads and evolving requirements. Additionally, it can limit the achievement of fault tolerance, a crucial aspect of ensuring safety in safety-critical systems. To address these limitations, this thesis focuses on developing fault tolerance and energy-saving techniques tailored explicitly for NoC-based multi-core architectures to enhance their safety and energy efficiency. The main goal is to incorporate fault tolerance mechanisms, such as adaptation and redundancy, into time-triggered systems without compromising the benefits of static resource allocation. The adaptation technique within the NoC is designed to support multiple schedules, allowing the NoC to switch schedules during run-time in response to context events, such as permanent faults in NoC resources (e.g., routers, links, network interfaces, and cores). By dynamically reconfiguring the schedule upon the occurrence of a permanent fault, the faulty component is effectively isolated, and tasks or messages are redistributed to other available resources. This ensures the system’s operational continuity despite faults that could lead to message corruption, delays, or losses within NoC resources. This adaptation technique improves the system’s safety by providing flexibility in resource allocation without sacrificing the benefits of static resource allocation. Furthermore, this thesis incorporates seamless redundancy techniques to enhance the system’s safety, especially in scenarios involving transient and permanent faults. This technique selectively applies message replication and fusion to safety-critical messages at the network interface, minimizing overhead in non-critical parts of the system. It safeguards critical data from potential failures caused by message corruption, delays, and losses in routers or links during message exchanges. The thesis also focuses on improving energy efficiency in multi-core chips by providing low-power services. By incorporating time-triggered communication into NoC-based multi-core architectures, deterministic communication is achieved by scheduling the message’s injection time and specifying the frequency to be used by each router at different points in time. This predetermined frequency in the schedule allows routers to adjust their frequencies accordingly during their active time and to clock gate the idle routers, enhancing energy efficiency and preserving the deterministic behaviour of the NoC communication. Moreover, the adaptation techniques in the NoC are used to reconfigure the operating frequency of the NoC based on workload or power requirement variations by switching between schedules, further optimizing energy consumption. Integrating features such as time-triggered capability, adaptation, time-triggered frequency scaling, and seamless redundancy mechanisms into NoC-based multi-core architectures represents a significant advancement over the current state of the art. The results of this work have significant implications for applications relying on high-performance, safe, and energy-efficient multi-core systems in various domains, such as healthcare and transportation.

Background: Predicting hypoglycemia in diabetes management remains a substantial challenge, especially for individuals with Type 1 Diabetes (T1D), advanced Type 2 Diabetes (T2D), and prediabetes. Existing prediction systems are largely dependent on continuous glucose monitoring (CGM) data and offer limited accuracy for extended prediction horizons. These systems often fail to account for the complex, individualized physiological variations inherent to each patient. Traditional monitoring methods are primarily invasive and lack the foresight needed for timely intervention. This limitation results in a heightened risk of severe complications and a significant decline in the quality of life (QoL) of patients with diabetes. Therefore, addressing these limitations requires an innovative, personalized, and multimodal approach to enhance the efficacy of hypoglycemia prediction and empower proactive diabetes management. Objectives: The core aim of this research is to develop and validate advanced predictive models for personalized hypoglycemia prediction through three primary domains: (i.) Methodological Development focused on advanced algorithm development, temporal modeling, and the creation of semantic frameworks to capture complex physiological interactions. (ii.) Data Integration and Analysis emphasizes multimodal data integration, the use of non-invasive monitoring approaches, and advanced pattern recognition to enhance the predictive power of the models. (iii.) the Implementation Framework aims at establishing personalization strategies, assessing clinical implementation, and optimizing technological solutions for embedding predictive models into wearable devices. Collectively, these objectives work towards an innovative, personalized, and practical approach to managing hypoglycemia in individuals with diabetes. Methods: This cumulative thesis synthesized findings from five peer-reviewed publications, utilizing data from three complementary datasets: D1NAMO (n=7, Type 1 Diabetes (T1D) patients), BIG IDEAs Lab (n=16, prediabetic individuals), and MIMIC-III (glucose-insulin paired data from 9 518 patients). Key methodologies included shapelet-based feature extraction to identify distinctive physiological patterns indicative of hypoglycemia and semantic integration using ontologies and knowledge graphs for enhanced data context. Both traditional machine learning (ML) and Deep Learning (DL) models, such as Fully Convolutional Network (FCN) and Residual Network (ResNet), were evaluated for their predictive capabilities. Model validation implemented holdout and leave-one-person-out cross-validation. This approach emphasized personalized performance, temporal alignment, and the integration of multimodal physiological signals to ensure robust, individualized hypoglycemia prediction. Results: This research resulted in several key advancements in predictive modeling for hypoglycemia: (1) The FCN achieved 97% accuracy in predicting the time-to-hypoglycemia, extending prediction horizons up to 48 hours; while the ResNet model achieved 94% accuracy, emphasizing the role of model architecture in optimizing prediction capabilities. (2) Temporal analysis revealed critical glucose normalization patterns within a 1–4 hour timeframe before hypoglycemic episodes, underscoring opportunities for preventive interventions. (3) Shapelet-based analysis revealed varying model performances: the three-layered Convolutional Neural Network (CNN) achieved 76% accuracy with heart rate data, while the two-layered CNN model reached 67% accuracy. In comparison, traditional machine learning (ML) approaches showed complementary strengths – Random Forest Classifier (RFC) demonstrated 73% accuracy with heart rate and 69% with breathing rate data, and Support Vector Machine (SVM) achieved 56% accuracy with heart rate and 65% with breathing rate data. These differences in performance demonstrated that advanced architecture optimization is vital for capturing personalized physiological responses. (4) Correlation analyses demonstrated substantial inter-individual variability in glucose-heart rate relationships, with correlation coefficients ranging from -0.4087 to 0.1882, thus highlighting the necessity for tailored modeling approaches. (5) Integration of a semantic framework, utilizing ontologies and knowledge graphs, uncovered previously undetectable patterns through structured representations of patient-specific factors. This structured knowledge representation contributed to improve interpretability and prediction capabilities. (6) Classification models with temporal pattern modeliing, adapted to patient-specific glucose fluctuations achieved accuracy rates ranging from 84% to 99% for different individuals, thus, highlighting the importance of personalization in predictive modeling. Conclusion: This research demonstrated that integrating multimodal physiological data, advanced temporal modeling, and semantic knowledge frameworks significantly enhances the prediction of hypoglycemic events. Also, by employing personalized modeling approaches, predictive accuracy per patient can be improved, enabling timely and patient-specific interventions. These advancements pave the way for transforming hypoglycemia prediction into a proactive and individualized system, ultimately contributing to better clinical outcomes and improved QoL for patients with diabetes.

Die Situation an den deutschen Hochschulen wird – wieder einmal – als krisenhaft beschrieben. Doch auch Veränderungen im Tertiärbereich sind nichts naturwüchsiges, sondern sie beruhen auf politischer Gestaltung. Die primär politisch anmutende Frage, welche Einflüsse aus dem Politik- und Rechtssystem, insbesondere aus der Gesellschaftsstruktur, der Kultur, der Wirtschaft sowie aus dem Bildungs- und Beschäftigungssystem und den Systemen zur privaten Lebensgestaltung auf die Hochschule als Institution allgemein und auf die Konstruktion von Studiengängen speziell wirken, ist auch aus pädagogischer Sicht von Bedeutung, da sie die Rahmenbedingungen für die personale Entwicklung von Studierenden in den Hochschulen –fördernd oder hemmend – (mit)gestalten. Unter Berücksichtigung von Entwicklungen in der Soziologie, Politikwissenschaft und Berufs- und Wirtschaftspädagogik ist ein Analysemodell für die akademische Berufsausbildung entwickelt worden, mit dessen Hilfe die Vorstellungen der (Regierungs)Parteien zu dieser Thematik anhand spezifischer Kriterien untersucht und verglichen wurden. Mit Hilfe dieses Analyseinstrumentariums wurden die gesellschaftlichen Ziele und Aufgaben, die für die Organisation der Hochschulen und für die Konstruktion von Studiengängen hochschulpolitisch diskutiert und gesetzt werden, transparent gemacht, systematisiert und auf Konsensmöglichkeiten geprüft. Darüber hinaus werden abschließend erste Hinweise auf berufs- und wirtschaftspädagogisch wünschenswerte Gestaltungsoptionen für die akademische Berufsausbildung gegeben und es wird auf diesbezügliche Forschungsdesiderate hingewiesen.