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This dissertation presents a probabilistic state estimation framework for integrating data-driven machine learning models and a deformable facial shape model in order to estimate continuous-valued intensities of 22 different facial muscle movements, known as Action Units (AU), defined in the Facial Action Coding System (FACS). A practical approach is proposed and validated for integrating class-wise probability scores from machine learning models within a Gaussian state estimation framework. Furthermore, driven mass-spring-damper models are applied for modelling the dynamics of facial muscle movements. Both facial shape and appearance information are used for estimating AU intensities, making it a hybrid approach. Several features are designed and explored to help the probabilistic framework to deal with multiple challenges involved in automatic AU detection. The proposed AU intensity estimation method and its features are evaluated quantitatively and qualitatively using three different datasets containing either spontaneous or acted facial expressions with AU annotations. The proposed method produced temporally smoother estimates that facilitate a fine-grained analysis of facial expressions. It also performed reasonably well, even though it simultaneously estimates intensities of 22 AUs, some of which are subtle in expression or resemble each other closely. The estimated AU intensities tended to the lower range of values, and were often accompanied by a small delay in onset. This shows that the proposed method is conservative. In order to further improve performance, state-of-the-art machine learning approaches for AU detection could be integrated within the proposed probabilistic AU intensity estimation framework.
With the digital transformation, software systems have become an integral part of our society and economy. In every part of our life, software systems are increasingly utilized to, e.g., simplify housework or to optimize business processes. All these applications are connected to the Internet, which already includes millions of software services consumed by billions of people. Applications which process such a magnitude of users and data traffic requires to be highly scalable and are therefore denoted as Ultra Large Scale (ULS) systems. Roy Fielding has defined one of the first approaches which allows designing modern ULS software systems. In his doctoral thesis, Fielding introduced the architectural style Representational State Transfer (REST) which builds the theoretical foundation of the web. At present, the web is considered as the world's largest ULS system. Due to a large number of users and the significance of software for society and the economy, the security of ULS systems is another crucial quality factor besides high scalability.
Due to the use of fossil fuel resources, many environmental problems have been increasingly growing. Thus, the recent research focuses on the use of environment friendly materials from sustainable feedstocks for future fuels, chemicals, fibers and polymers. Lignocellulosic biomass has become the raw material of choice for these new materials. Recently, the research has focused on using lignin as a substitute material in many industrial applications. The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. DPPH assay was used to determine the antioxidant activity of Kraft lignin compared to Organosolv lignins from different biomasses. The purification procedure of Kraft lignin showed that double-fold selective extraction is the most efficient confirmed by UV-Vis, FTIR, HSQC, 31PNMR, SEC, and XRD. The antioxidant capacity was discussed regarding the biomass source, pulping process, and degree of purification. Lignin obtained from industrial black liquor are compared with beech wood samples: Biomass source influences the DPPH inhibition (softwood > grass) and the TPC (softwood < grass). DPPH inhibition affected by the polarity of the extraction solvent. Following the trend: ethanol > diethylether > acetone. Reduced polydispersity has positive influence on the DPPH inhibition. Storage decreased the DPPH inhibition but increased the TPC values. The DPPH assay was also used to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. In both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems the 5% addition showed the highest activity and the highest addition had the lowest. Both scavenging activity and antimicrobial activity are dependent on the biomass source; Organosolv of softwood > Kraft of softwood > Organosolv of grass. Lignins and lignin-containing films showed high antimicrobial activities against Gram-positive and Gram-negative bacteria at 35 °C and at low temperatures (0-7 °C). Purification of Kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin leaching in the produced films affected the activity positively and the chitosan addition enhances the activity for both Gram-positive and Gram-negative bacteria. Testing the films against food spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films, the 5% addition exhibited activity against both food spoilage bacteria.
For a sustainable development the electricity sector needs to be decarbonized. In 2017 only 54% of the West African households had access to the electrical grid. Thus, renewable sources should play a major role for the development of the power sector in West Africa. Above all, solar power shows highest potential of renewable energy sources. However, it is highly variable, depending on the atmospheric conditions. This study addresses the challenges for a solar based power system in West Africa by analyzing the atmospheric variability of solar power. For this purpose, two aspects are investigated. In the first part, the daily power reduction due to atmospheric aerosols is quantified for different solar power technologies. Meteorological data at six ground-based stations is used to model photovoltaic and parabolic trough power during all mostly clear-sky days in 2006. A radiative transfer model is combined with solar power model. The results show, that the reduction due to aerosols can be up to 79% for photovoltaic and up to 100% for parabolic trough power plants during a major dust outbreak. Frequent dust outbreaks occurring in West Africa would cause frequent blackouts if sufficient storage capacities are not available. On average, aerosols reduce the daily power yields by 13% to 22% for photovoltaic and by 22% to 37% for parabolic troughs. For the second part, long-term atmospheric variability and trends of solar irradiance are analyzed and their impact on photovoltaic yields is examined for West Africa. Based on a 35-year satellite data record (1983 - 2017) the temporal and spatial variability and general trend are depicted for global and direct horizontal irradiances. Furthermore, photovoltaic yields are calculated on a daily basis. They show a strong meridional gradient with highest values of 5 kWh/kWp in the Sahara and Sahel zone and lowest values in southern West Africa (around 4 kWh/kWp). Thereby, the temporal variability is highest in southern West Africa (up to around 18%) and lowest in the Sahara (around 4.5%). This implies the need of a North-South grid development, to feed the increasing demand on the highly populated coast by solar power from the northern parts of West Africa. Additionally, global irradiances show a long-term positive trend (up to +5 W/m²/decade) in the Sahara and a negative trend (up to -5 W/m²/decade) in southern West Africa. If this trend is continuing, the spatial differences in solar power potential will increase in the future. This thesis provides a better understanding of the impact of atmospheric variability on solar power in a challenging environment like West Africa, characterized by the strong influence of the African monsoon. Thereby, the importance of aerosols is pointed out. Furthermore, long-term changes of irradiance are characterized concerning their implications for photovoltaic power.
Bedingt durch die zunehmende Rohstoffknappheit rückt die Suche nach alternativen, nachhaltigen Rohstoffen immer mehr in den Vordergrund. Im Hinblick auf effiziente chemische Verwertbarkeit bietet Lignin zahlreiche Vorteile für verschiedene Anwendungsbereiche, beispielsweise für biobasierte Polyurethanbeschichtungen, etwa zum Korrosionsschutz. Wesentliche Probleme bei der Verwendung von Lignin ergeben sich durch die Heterogenität dieses Naturstoffes sowie durch dessen geringe Polymerisations-Kompatibilität mit Polyolefinen; beide Faktoren beeinflussen u. a die mechanischen Eigenschaften entsprechender Lignin-basierter Polymere. Zudem hängt die konkrete Struktur und damit auch die physikalisch/chemischen Eigenschaften des Lignins stark von der jeweiligen Rohstoffquelle sowie dem Extraktionsverfahren ab.
Ziel dieser Arbeit war die Strukturaufklärung unmodifizierter und modifizierter Kraft-Lignine (KL) und die Untersuchung der Reaktivität aromatischer wie aliphatischer Hydroxygruppen in Abhängigkeit vom pH-Wert. Hierzu wurden unmodifizierte KL aus Schwarzlauge extrahiert und nachfolgend zunächst einer Soxhlet-Extraktion unterzogen, um in Methyltetrahydrofuran lösliche Lignin-Bestandteile – vornehmlich mit aromatischem Charakter – zu gewinnen und so eine verbesserte Löslichkeit auch im bei der nachfolgenden Polyurethansynthese als Lösemittel verwendeten THF zu gewährleisten. Überdies wurden die extrahierten KL via Demethylierung von Methoxygruppen chemisch modifiziert. Zudem wurde mittels nasschemischer Methoden sowie mit differentieller UV/VIS-Spektroskopie die Anzahl an für die Polymerisation erforderliche Hydroxygruppen quantifiziert. Im Anschluss erfolgte, unter besonderer Berücksichtigung ökologischer und ökonomischer Nachhaltigkeitsaspekte, die Synthese Lignin-basierter und funktionalisierter Polyurethanbeschichtungen. Die Oberflächenfunktionalisierung gestattete die Verbesserung der Oberflächenhomogenität sowie - via blend formation - das Einbetten von TPM-Farbstoffen in die Coatings. Hinsichtlich des Einflusses des bei der Extraktion gewählten pH-Wertes (pH = 2 - 5) auf das Verhalten der so gewonnenen KL wurde eine Veränderung sowohl der Struktur der Lignine als auch deren thermischer Stabilität beobachtet. Zudem wurde nachgewiesen, dass mit steigendem pH-Wert die Funktionalität/Reaktivität der aromatischen wie aliphatischen Hydroxygruppen im Lignin zunimmt. Aus unmodifiziertem KL wurden erfolgreich homogene Lignin-basierte Polyurethan-Coatings (LPU-Coatings) synthetisiert; diese LPU-Coatings zeigten bei Verwendung von bei höheren pH-Werten extrahierten KL homogenere, hydrophobe Oberflächenbeschaffenheit sowie gute thermische Stabilität. Zusätzliche Modifizierung der KL durch Demethylierung führte wegen der gesteigerten Anzahl freier Hydroxygruppen zu moderater Reaktivitätssteigerung und damit zu weiterer Verbesserung der Oberflächeneigenschaften hinsichtlich einer homogenen Oberflächenstruktur und -brillanz. Im Hinblick auf den Aspekt der Nachhaltigkeit wurden durch Syntheseoptimierung - bestehend aus Einstellung der Rohstoff-Korngröße, Ultraschallbehandlung und Verwendung des kommerziellen trifunktionellen Polyetherpolyols Lupranol® 3300 in Kombination mit Desmodur® L75 - die Löslichkeit von Lignin im Polyol sowie die thermische Stabilität der LPU-Coatings erhöht. Im Zuge der Syntheseoptimierungen konnte durch verkürzte Trocknungszeiten Energieeinsparung erzielt werden; zudem ließen sich dabei die eingesetzten Mengen kommerziell erhältlicher Chemikalien verringern; beide Einsparungen führten zu Kostenreduktion. Zugleich ließ sich so nicht nur der KL-Anteil im Polymer-Coating erhöhen: Durch eine optimierte wirtschaftliche Einstufensynthese ließ sich die Umsetzung dieser Vorgehensweise auch im Rahmen industrieller Anwendungen vereinfachen. Das Einbetten ausgewählter TPM-Farbstoffe (Kristallviolett und Brilliantgrün) in die LPU-Coatings durch blend formation führte nachweislich zu antimikrobieller Wirkung der Oberflächenbeschichtung, ohne dass die Oberflächenbeschaffenheit an Homogenität verlor. Die im Rahmen dieser Arbeit synthetisierten LPU-Coatings könnten zukünftig als Korrosionsschutz- und antimikrobielle-Beschichtungen ihre Anwendung finden, z. B. in der Landwirtschaft und im Bausektor.
Die im Rahmen der vorliegenden Arbeit gewonnen Erkenntnisse liefern einen Beitrag zur strukturellen Aufklärung des komplexen Biopolymers Lignin. Darüber hinaus stellen die Untersuchungen und Ergebnisse eine Grundlage für eine nachhaltige Herstellung von Lignin-basierten Polymerbeschichtungen dar, die in Zukunft immer mehr an Bedeutung gewinnen werden.
Optimization plays an essential role in industrial design, but is not limited to minimization of a simple function, such as cost or strength. These tools are also used in conceptual phases, to better understand what is possible. To support this exploration we focus on Quality Diversity (QD) algorithms, which produce sets of varied, high performing solutions. These techniques often require the evaluation of millions of solutions -- making them impractical in design cases. In this thesis we propose methods to radically improve the data-efficiency of QD with machine learning, enabling its application to design. In our first contribution, we develop a method of modeling the performance of evolved neural networks used for control and design. The structures of these networks grow and change, making them difficult to model -- but with a new method we are able to estimate their performance based on their heredity, improving data-efficiency by several times. In our second contribution we combine model-based optimization with MAP-Elites, a QD algorithm. A model of performance is created from known designs, and MAP-Elites creates a new set of designs using this approximation. A subset of these designs are the evaluated to improve the model, and the process repeats. We show that this approach improves the efficiency of MAP-Elites by orders of magnitude. Our third contribution integrates generative models into MAP-Elites to learn domain specific encodings. A variational autoencoder is trained on the solutions produced by MAP-Elites, capturing the common “recipe” for high performance. This learned encoding can then be reused by other algorithms for rapid optimization, including MAP-Elites. Throughout this thesis, though the focus of our vision is design, we examine applications in other fields, such as robotics. These advances are not exclusive to design, but serve as foundational work on the integration of QD and machine learning.
Discrimination and classification of eight strains related to meat spoilage microorganisms commonly found in poultry meat were successfully carried out using two dispersive Raman spectrometers (Microscope and Portable Fiber-Optic systems) in combination with chemometric methods. Principal Components Analysis (PCA) and Multi-Class Support Vector Machines (MC-SVM) were applied to develop discrimination and classification models. These models were certified using validation data sets which were successfully assigned to the correct bacterial genera and even to the right strain. The discrimination of bacteria down to the strain level was performed for the pre-processed spectral data using a 3-stage model based on PCA. The spectral features and differences among the species on which the discrimination was based were clarified through PCA loadings. In MC-SVM the pre-processed spectral data was subjected to PCA and utilized to build a classification model. When using the first two components, the accuracy of the MC-SVM model was 97.64% and 93.23% for the validation data collected by the Raman Microscope and the Portable Fiber-Optic Raman system, respectively. The accuracy reached 100% for the validation data by using the first eight and ten PC’s from the data collected by Raman Microscope and by Portable Fiber-Optic Raman system, respectively. The results reflect the strong discriminative power and the high performance of the developed models, the suitability of the pre-processing method used in this study and that the low accuracy of the Portable Fiber-Optic Raman system does not adversely affect the discriminative power of the developed models.
Neben der individuellen Bedeutung von Gesundheit für jeden Menschen, steigt auch die Relevanz von „gesunden Beschäftigten“. Gerade in Zeiten von Vollbeschäftigung, Fachkräftemangel und höherem Renteneintrittsalter, rückt die Gesundheit der Beschäftigten und die damit verbundene Arbeitsfähigkeit jedes Einzelnen stärker in den Fokus. Staat, Sozialversicherungsträger und Unternehmen sind zunehmend daran interessiert, Arbeitsplätze und Arbeitsbedingungen gesundheitsförderlich zu gestalten. Hierbei bildet die BGF den Rahmen für die existierenden gesundheitsförderlichen Interventionen, die in einer Vielzahl im betrieblichen Setting vorzufinden sind. Die Arbeitspause kann in diesem Kontext als geeignete Intervention angesehen werden, die jedoch sehr vielfältig in der Ausgestaltung sein kann.
In forensic DNA profiling, the occurrence of complex mixed profiles is currently a common issue. Cases involving intimate swabs or skin flake tape liftings are prone to mixed profiles, because of more than one donor contributing to a DNA sample. By DNA profiling of single spermatozoa and skin flakes, problems associated with mixed profile could ideally be overcome. However, PCR is not a sensitive enough method to generate DNA profiles by STRs on single cells. Moreover, high quality intact DNA is required, but is not always available in skin flakes due to degradation. Additionally, single skin flakes are difficult to discriminate from other similar looking particles on tape liftings used to secure DNA samples from evidence. The main purpose of this study was to develop a method that enables DNA profiling of single sperm cells and skin flakes. After studying multiple whole genome amplification (WGA) protocols, REPLI-g Single Cell WGA was selected due to its suitability in the pre-amplification step of template DNA. Micromanipulation was used to isolate single spermatozoa. Furthermore, micromanipulation in combination with REPLI-g Single Cell WGA resulted in successful DNA profiling of single spermatozoa by using autosomal STRs as well as X- and Y-chromosomal STRs. The single spermatozoa DNA profiling method described in this thesis was successfully used to identify male contributors from mock intimate swabs with a mixture of semen from multiple male contributors. Different dyes were analysed to develop a staining method to discriminate skin flakes from other particles including particles such as those from hair cosmetic products. From all dyes tested, Orange G was the only dye which successfully discriminated skin flakes from hair product particles. Also, an alkaline based lysis protocol was developed that allowed PCR to be carried out directly on the lysates of single skin flakes. Furthermore, REPLI-g Single Cell WGA was tested on single skin flakes. In contrast to the single spermatozoa, REPLI-g Single Cell WGA was not successful in DNA profiling of single skin flakes. The single skin flake DNA profiling method described in this thesis was successfully used in correctly identifying contributors from mock mixed DNA evidence. Additionally, a small amplicon-based NGS method was tested on single skin flakes. Compared to the PCR and CE approach, the small amplicon-based NGS method improved DNA profiling of single skin flakes, giving a significant increase in allele recovery. In conclusion, this study shows circumventing mixtures is possible by DNA profiling of single spermatozoa, using micromanipulation and WGA. Furthermore, DNA profiling of single skin flakes has been improved by the staining of tape liftings methodology with Orange G, alkaline lysis, direct-PCR and a small amplicon-based NGS approach. Nonetheless, future work is required to assess the performance of the single spermatozoa method on mock swabs with more diluted semen. Also, commercially available NGS kits should be tested with single skin flakes and compared with the in-house NGS method.
Due to the popularity of the Internet and the networked services that it facilitates, networked devices have become increasingly common in both the workplace and everyday life in recent years—following the trail blazed by smartphones. The data provided by these devices allow for the creation of rich user profiles. As a result, the collection, processing and exchange of such personal data have become drivers of economic growth. History shows that the adoption of new technologies is likely to influence both individual and societal concepts of privacy. Research into privacy has therefore been confronted with continuously changing concepts due to technological progress. From a legal perspective, privacy laws that reflect social values are sought. Privacy enhancing technologies are developed or adapted to take account of technological development. Organizations must also identify protective measures that are effective in terms of scalability and automation. Similarly, research is being conducted from the perspective of Human-Computer Interaction (HCI) to explore design spaces that empower individuals to manage their protection needs with regard to novel data, which they may perceive as sensitive. Taking such an HCI perspective with regard to understanding privacy management on the Internet of Things (IoT), this research mainly focuses on three interrelated goals across the fields of application: 1. Exploring and analyzing how people make sense of data, especially when managing privacy and data disclosure; 2. Identifying, framing and evaluating potential resources for designing sense-making processes; and 3. Exploring the fitness of the identified concepts for inclusion in legal and technical perspectives on supporting decisions regarding privacy on the IoT. Although this work's point of departure is the HCI perspective, it emphasizes the importance of the interrelationships among seemingly independent perspectives. Their interdependence is therefore also emphasized and taken into account by subscribing to a user-centered design process throughout this study. More specifically, this thesis adopts a design case study approach. This approach makes it possible to conduct full user-centered design lifecycles in a concrete application case with participants in the context of everyday life. Based on this approach, it was possible to investigate several domains of the IoT that are currently relevant, namely smart metering, smartphones, smart homes and connected cars. The results show that the participants were less concerned about (raw) data than about the information that could potentially be derived from it. Against the background of the constant collection of highly technical and abstract data, the content of which only becomes visible through the application of complex algorithms, this study indicates that people should learn to explore and understand these data flexibly, and provides insights in how to design for supporting this aim. From the point of view of design for usable privacy protection measures, the information that is provided to users about data disclosure should be focused on the consequences thereof for users' environments and life. A related concept from law is “informed consent,” which I propose should be further developed in order to implement usable mechanisms for individual privacy protection in the era of the IoT. Finally, this thesis demonstrates how research on HCI can be methodologically embedded in a regulative process that will inform both the development of technology and the drafting of legislation.
Solving differential-algebraic equations (DAEs) efficiently by means of appropriate numerical schemes for time-integration is an ongoing topic in applied mathematics. In this context, especially when considering large systems that occur with respect to many fields of practical application effective computation becomes relevant. In particular, corresponding examples are given when having to simulate network structures that consider transport of fluid and gas or electrical circuits. Due to the stiffness properties of DAEs, time-integration of such problems generally demands for implicit strategies. Among the schemes that prove to be an adequate choice are linearly implicit Rung-Kutta methods in the form of Rosenbrock-Wanner (ROW) schemes. Compared to fully implicit methods, they are easy to implement and avoid the solution of non-linear equations by including Jacobian information within their formulation. However, Jacobian calculations are a costly operation. Hence, necessity of having to compute the exact Jacobian with every successful time-step proves to be a considerable drawback. To overcome this drawback, a ROW-type method is introduced that allows for non-exact Jacobian entries when solving semi-explicit DAEs of index one. The resulting scheme thus enables to exploit several strategies for saving computational effort. Examples include using partial explicit integration of non-stiff components, utilizing more advantageous sparse Jacobian structures or making use of time-lagged Jacobian information. In fact, due to the property of allowing for non-exact Jacobian expressions, the given scheme can be interpreted as a generalized ROW-type method for DAEs. This is because it covers many different ROW-type schemes known from literature. To derive the order conditions of the ROW-type method introduced, a theory is developed that allows to identify occurring differentials and coefficients graphically by means of rooted trees. Rooted trees for describing numerical methods were originally introduced by J.C. Butcher. They significantly simplify the determination and definition of relevant characteristics because they allow for applying straightforward procedures. In fact, the theory presented combines strategies used to represent ROW-type methods with exact Jacobian for DAEs and ROW-type methods with non-exact Jacobian for ODEs. For this purpose, new types of vertices are considered in order to describe occurring non-exact elementary differentials completely. The resulting theory thus automatically comprises relevant approaches known from literature. As a consequence, it allows to recognize order conditions of familiar methods covered and to identify new conditions. With the theory developed, new sets of coefficients are derived that allow to realize the ROW-type method introduced up to orders two and three. Some of them are constructed based on methods known from literature that satisfy additional conditions for the purpose of avoiding effects of order reduction. It is shown that these methods can be improved by means of the new order conditions derived without having to increase the number of internal stages. Convergence of the resulting methods is analyzed with respect to several academic test problems. Results verify the theory determined and the order conditions found as only schemes satisfying the order conditions predicted preserve their order when using non-exact Jacobian expressions.
The present thesis elucidates the development of (i) a series of small molecule inhibitors reacting in a covalent-irreversible manner with the targeted proteases and (ii) a fluorescently labeled activity-based probe as a pharmacological tool compound for investigation of specific functions of the mentioned enzymes in vitro. Herein, the rational design, organic synthesis and quantitative structure-activity-relationships are described extensively.
The globalisation and the increasing international trade have raised the number and risk of introduction of foreign species and invasive pests for years. Although native species have adapted to the native habitat over many years and generations, invasive intruders often possess characteristics that are superior to native species. Thus, and because of a lack of natural enemies, they bear the potential of decimation or complete displacement of the native species; furthermore, the introduction of pathogens or nematodes as a vector possesses a high damage potential. The available measures of the local plant protection services to combat invasive species are confined. They are limited to the felling of infested trees or plants and regular controls within the infested area. A spread of single infestations can thereby be prevented, but undetected infestations can unimpededly spread, which points out the main challenge: the detection of the species. This concerns the infestation in open land as well as the single animal on its path of introduction. Concerning the development of new adequate detection systems for invasive species, there is only little research activity going on. For other fields like detection of explosives or narcotics, the research activities date back for more than one decade and consequently there are detection systems available, which are, for example, used for explosive detection in airports. The detection principle bases on the chemistry of these substances.
Evaluation and Optimization of IEEE802.11 multi-hop Backhaul Networks with Directional Antennas
(2020)
A major problem for rural areas is the inaccessibility to affordable broadband Internet connections. In these areas distances are large, and digging a cable into the ground is extremely expensive, considering the small number of potential customers at the end of that cable. This leads to a digital divide, where urban areas enjoy a high-quality service at low cost, while rural areas suffer from the reverse.
This work is dedicated to an alternative technical approach aiming to reduce the cost for Internet Service Provider in rural areas: WiFi-based Long Distance networks. A set of significant contributions of technology related aspects of WiFi-based Long Distance networks is described in three different fields: Propagation on long distance Wi-Fi links, MAC-layer scheduling and Interference modeling and Channel Assignment with directional antennas.
For each field, the author composes and discusses the state-of-the-art. Afterwards, the author derives research questions and tackles several open issues to develop these kinds of networks further towards a suitable technology for the backhaul segment.