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Five personality traits commonly known as the “Big Five” have been widely acknowledged as universal. But most available psychological instruments are not necessarily transferable to other cultures. They are referred to as “W.E.I.R.D.” (western, educated, industrial, rich, democratic) and lack the combined emic-etic approach that is necessary for a transcultural perspective. This intercontinental congress brings experts from Kenya and Germany together – thinking out of the box and collecting ideas for a scientific based partnership of East Africa and Europe. Main topics are psychological constructs that prove relevant for Human Resources Management. The Five-Factor Model, core self-evaluations, coping processes and acculturation as well as globalization effects and gender issues are discussed.
This thesis presents novel approaches for integrating context information into probabilistic models. Data from social media is typically associated with metadata, which includes context information such as timestamps, geographical coordinates or links to user profiles. Previous studies showed the benefits of using such context information in probabilistic models, e.g.\ improved predictive performance. In practice, probabilistic models which account for context information still play a minor role in data analysis. There are multiple reasons for this. Existing probabilistic models often are complex, the implementation is difficult, implementations are not publicly available, or the parameter estimation is computationally too expensive for large datasets. Additionally, existing models are typically created for a specific type of content and context and lack the flexibility to be applied to other data.
This thesis addresses these problems by introducing a general approach for modelling multiple, arbitrary context variables in probabilistic models and by providing efficient inference schemes and implementations.
In the first half of this thesis, the importance of context and the potential of context information for probabilistic modelling is shown theoretically and in practical examples. In the second half, the example of topic models is employed for introducing a novel approach to context modelling based on document clusters and adjacency relations in the context space. They can cope with areas of sparse observations and These models allow for the first time the efficient, explicit modelling of arbitrary context variables including cyclic and spherical context (such as temporal cycles or geographical coordinates). Using the novel three-level hierarchical multi-Dirichlet process presented in this thesis, the adjacency of ontext clusters can be exploited and multiple contexts can be modelled and weighted at the same time. Efficient inference schemes are derived which yield interpretable model parameters that allow analyse the relation between observations and context.
Bei der Olivenölproduktion fallen innerhalb kürzester Zeit große Mengen Olivenabwasser (OMW) an. OMW kann aufgrund seines hohen Nährstoffgehalts als landwirtschaftlicher Dünger eingesetzt werden. Doch seine öligen und phenolischen Bestandteile schaden dem Boden. Es ist nicht bekannt, inwiefern jahreszeitliche Temperatur- und Niederschlagsschwankungen den Verbleib und die Wirkung der Abwasserkomponenten im Boden längerfristig beeinflussen. Um dem nachzugehen, wurden jeweils 14 L OMW m-2 im Winter, Frühling und Sommer auf verschiedenen Parzellen einer Olivenplantage ausgebracht. Hydrologische Bodeneigenschaften (Wassertropfeneindringzeit, Wasserleitfähigkeit, Kontaktwinkel), physikalisch-chemische Parameter (pH, EC, lösliche Ionen, phenolische Verbindungen, organischer Kohlenstoff) sowie der biologische Abbau (Köderstreifen) wurden erfasst, um den Zustand des Bodens nach der Applikation zu beurteilen. Nach einer Regensaison war die Bodenqualität der im Sommer behandelten Flächen signifikant reduziert. Dies wurde insbesondere anhand einer dreimal niedrigeren biologischen Fraßaktivität, zehnmal höherer Hydrophobizität, sowie einem viermal höheren Gehalt an phenolischen Substanzen im Vergleich zu den Kontrollflächen deutlich. Die Ausbringung im Winter zeigte gegenteilige Effekte, welche das natürliche Regenerierungspotential des Bodens erkennen lassen. Der Einfluss der Frühlingsapplikation lag zwischen den zuvor genannten. Es wurden keinerlei Anzeichen auf Verlagerung von OMW-Bestandteilen in tiefere Bodenschichten beobachtet. Während der feuchten Jahreszeiten gilt die Ausbringung gesetzlich begrenzter Mengen Olivenabwasser somit als vertretbar. Weitere Forschung ist notwendig um den Einfluss von Frühlingsapplikationen zu quantifizieren und weitere Erkenntnisse über die Zusammensetzung und Mobilität organischer OMW-Bestandteile im Boden zu gewinnen.
In Part I: "The flow-decomposition problem", we introduce and discuss the flow-decomposition problem. Given a flow F, this problem consists of decomposing the flow into a set of paths optimizing specific properties of those paths. We introduce different types of decompositions, such as integer decompositions and alpha-decompositions, and provide two formulations of the set of feasible decompositions.
We show that the problem of minimizing the longest path in a decomposition is NP-hard, even for fractional solutions. Then we develop an algorithm based on column generation which is able to solve the problem.
Tight upper bounds on the optimal objective value help to improve the performance.
To find upper bounds on the optimal solution for the shortest longest path problem, we develop several heuristics and analyze their quality. On pearl graphs we prove a constant approximation ratio of 2 and 3 respectively for all heuristics. A numerical study on random pearl graphs shows that the solutions generated by the heuristics are usually much better than this worst-case bound.
In Part II: "Construction and analysis of evacuation models using flows over time", we consider two optimization models in the context of evacuation planning. The first model is a parameter-based quickest flow model with time-dependent supply values. We give a detailed description of the network construction and of how different scenarios are modeled by scenario parameters. In a second step we analyze the effect of the scenario parameters on the evacuation time. Understanding how the different parameters influence the evacuation time allows us to provide better advice for evacuation planning and allows us to predict evacuation times without solving additional optimization problems. To understand the effect of the time-dependent supply values, we consider the quickest path problem with time-dependent supply values and provide a solution algorithm. The results from this consideration are generalized to approximate the behavior of the evacuation times in the context of quickest flow problems.
The second model we consider is a path-based model for evacuation in the presence of a dynamic cost function. We discuss the challenges of this model and provide ideas for how to approach the problem from different angles. We relate the problem to the flow-decomposition problem and consider the computation of evacuation paths with dynamic costs for large capacities. For the latter method we provide heuristics to find paths and compare them to the optimal solutions by applying the methods to two evacuation scenarios. An analysis shows that the paths generated by the heuristic yield close to optimal solutions and in addition have several desirable properties for evacuation paths which are not given for the optimal solution.
While reading this sentence, you probably gave (more or less deliberately) instructions to approximately 100 to 200 muscles of your body. A sceptical face or a smile, your fingers scrolling through the text or holding a printed version of this work, holding your head, sitting, and much more.
All these processes take place almost automatically, so they seem to be no real achievement. In the age of digitalization it is a defined goal to transfer human (psychological and physiological) behavior to machines (robots). However, it turns out that it is indeed laborious to obtain human facial expression or walking from robots. To optimize this transfer, a deeper understanding of a muscle's operating principle is needed (and of course an understanding of the human brain, which will, however, not be part of this thesis).
A human skeletal muscle can be shortened willingly, but not lengthened, thereto it takes an antagonist. The muscle's change in length is dependent on the incoming stimulus from the central nervous system, the current length of the muscle itself, and certain muscle--specific quantities (parameters) such as the maximum force. Hence, a muscle can be mathematically described by a differential equation (or more exactly a coupled differential--algebraic system, DAE), whose structure will be revealed in the following chapters. The theory of differential equations is well-elaborated. A multitude of applicable methods exist that may not be known by muscle modelers. The purpose of this work is to link the methods from applied mathematics to the actual application in biomechanics.
The first part of this thesis addresses stability theory. Let us remember the prominent example from middle school physics, in which the resting position of a ball was obviously less susceptible towards shoves when lying in a bowl rather than balancing at the tip of a hill. Similarly, a dynamical (musculo-skeletal) system can attain equilibrium states that react differently towards perturbations.
We are going to compute and classify these equilibria.
In the second part, we investigate the influence of individual parameters on model equations or more exactly their solutions. This method is known as sensitivity analysis.
Take for example the system "car" containing a value for the quantity "pressure on the break pedal while approaching a traffic light". A minor deviation of this quantity upward or downward may lead to an uncomfortable, abrupt stop or even to a collision, instead of a smooth stop with a sufficient gap.
The considered muscle model contains over 20 parameters that, if changed slightly, have varying effects on the model equation solutions at different instants of time. We will investigate the sensitivity of those parameters regarding different sub--models, as well as the whole model among different dynamical boundary conditions.
The third and final part addresses the \textit{optimal control} problem (OCP).
The muscle turns a nerve impulse (input or control) into a length change and therefore a force response (output). This forward process is computable by solving the respective DAE. The reverse direction is more difficult to manage. As an everyday example, the OCP is present regarding self-parking cars, where a given path is targeted and the controls are the position of the
steering wheel as well as the gas pedal.
We present two methods of solving OCPs in muscle modeling: the first is a conjunction of variational calculus and optimization in function spaces, the second is a surrogate-based optimization.
While Virtual Reality has been around for decades it gained new life in recent years. The release of the first consumer hardware devices allows fully immersive and affordable VR for the user at home. This availability lead to a new focus of research on technical problems as well as psychological effects. The concepts of presence, describing the feeling of being in the virtual place, body ownership and their impact are central topics in research for a long time and still not fully understood.
To enable further research in the area of Mixed Reality, we want to introduce a framework that integrates the users body and surroundings inside a visual coherent virtual environment. As one of two main aspects we want to merge real and virtual objects to a shared environment in a way such that they are no longer visually distinguishable. To achieve this the main focus is not supposed to be on a high graphical fidelity but on a simplified representation of reality. The essential question is, what level of visual realism is necessary to create a believable mixed reality environment that induces a sense of presence in the user? The second aspect considers the integration of virtual persons. Can characters be recorded and replayed in a way such that they are perceived as believable entities of the world and therefore act as a part of the users environment?
The purpose of this thesis was the development of a framework called Mixed Reality Embodiment Platform. This inital system implements fundamental functionalities to be used as a basis for future extensions to the framework. We also provide a first application that enables user studies to evaluate the framework and contribute to aforementioned research questions.
Conversion of natural vegetation into cattle pastures and croplands results in altered emissions of greenhouse gases (GHG), such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Their atmospheric concentration increase is attributed the main driver of climate change. Despite of successful private initiatives, e.g. the Soy Moratorium and the Cattle Agreement, Brazil was ranked the worldwide second largest emitter of GHG from land use change and forestry, and the third largest emitter from agriculture in 2012. N2O is the major GHG, in particular for the agricultural sector, as its natural emissions are strongly enhanced by human activities (e.g. fertilization and land use changes). Given denitrification the main process for N2O production and its sensitivity to external changes (e.g. precipitation events) makes Brazil particularly predestined for high soil-derived N2O fluxes.
In this study, we followed a bottom-up approach based on a country-wide literature research, own measurement campaigns, and modeling on the plot and regional scale, in order to quantify the scenario-specific development of GHG emissions from soils in the two Federal States Mato Grosso and Pará. In general, N2O fluxes from Brazilian soils were found to be low and not particularly dynamic. In addition to that, expected reactions to precipitation events stayed away. These findings emphasized elaborate model simulations in daily time steps too sophisticated for regional applications. Hence, an extrapolation approach was used to first estimate the influence of four different land use scenarios (alternative futures) on GHG emissions and then set up mitigation strategies for Southern Amazonia. The results suggested intensification of agricultural areas (mainly cattle pastures) and, consequently, avoided deforestation essential for GHG mitigation.
The outcomes of this study provide a very good basis for (a) further research on the understanding of underlying processes causing low N2O fluxes from Brazilian soils and (b) political attempts to avoid new deforestation and keep GHG emissions low.
The publication of open source software aims to support the reuse, the distribution and the general utilization of software. This can only be enabled by the correct usage of open source software licenses. Therefore associations provide a multitude of open source software licenses with different features, of which a developer can choose, to regulate the interaction with his software. Those licenses are the core theme of this thesis.
After an extensive literature research, two general research questions are elaborated in detail. First, a license usage analysis of licenses in the open source sector is applied, to identify current trends and statistics. This includes questions concerning the distribution of licenses, the consistency in their usage, their association over a period of time and their publication.
Afterwards the recommendation of licenses for specific projects is investigated. Therefore, a recommendation logic is presented, which includes several influences on a suitable license choice, to generate an at most applicable recommendation. Besides the exact features of a license of which a user can choose, different methods of ranking the recommendation results are proposed. This is based on the examination of the current situation of open source licensing and license suggestion. Finally, the logic is evaluated on the exemplary use-case of the 101companies project.
This study had two main aims. The first one was to investigate the quality of lesson plans. Two important features of lesson plans were used as a basis to determine the quality of lesson plans. These are adaptability to preconditions and cognitive activation of students. The former refers to how the planning teacher considers the diversity of students pre-existing knowledge and skills. The latter refers to how the planning teacher sequences deep learning tasks and laboratory activities to promote the cognitive activation of students.
The second aim of the study was to explore teachers thinking about and explanation of externally generated feedback data on their students’ performance. The emphasis here was to understand how the teachers anticipate planning differentiated lessons to accommodate the variations in students learning outcomes revealed by the feedback data.
The study followed a qualitative approach with multiple sources of data. Concept maps, questionnaires, an online lesson planning tool, standardized tests, and semi-structured interviews were the main data collection instruments used in the study. Participants of this study were four physics teachers teaching different grade levels. For the purpose of generating feedback for the participant teachers, a test was administered to 215 students. Teachers were asked to plan five lessons for their ongoing practices. The analysis showed that the planned lessons were not adapted to the diversity in students pre-existing knowledge and skills. The analysis also indicated that the lessons planned had limitations with regard to cognitive activation of students. The analysis of the interview data also revealed that the participant teachers do not normally consider differentiating lessons to accommodate the differences in students learning, and place less emphasis on the cognitive activation of students. The analysis of the planned lessons showed a variation in teachers approach in integrating laboratory activities in the sequence of the lessons ranging from a complete absence through a demonstrative to an investigative approach. Moreover, the findings from the interviews indicated differences between the participant teachers espoused theory (i.e. what they said during interview) and their theory- in –use (i.e. what is evident from the planned lessons). The analysis of the interview data demonstrated that teachers did not interpret the data, identify learning needs, draw meaningful information from the data for adapting (or differentiating) instruction. They attributed their students’ poor performance to task difficulty, students’ ability, students’ motivation and interest. The teachers attempted to use the item level and subscale data only to compare the relative position of their class with the reference group. However, they did not read beyond the data, like identifying students learning needs and planning for differentiated instruction based on individual student’s performance.
The work presented in this thesis investigated interactions of selected biophysical processes that affect zooplankton ecology at smaller scales. In this endeavour, the extent of changes in swimming behaviour and fluid disturbances produced by swimming Daphnia in response to changing physical environments were quantified. In the first research question addressed within this context, size and energetics of hydrodynamic trails produced by Daphnia swimming in non-stratified still waters were characterized and quantified as a function of organisms’ size and their swimming patterns.
The results revealed that neither size nor the swimming pattern of Daphnia affects the width of induced trails or dissipation rates. Nevertheless, as the size and swimming velocity of the organisms increased, trail volume increased in proportional to the cubic power of Reynolds number, and the biggest trail volume was about 500 times the body volume of the largest daphnids. Larger spatial extent of fluid perturbation and prolonged period to decay caused by bigger trail volumes would play a significant role in zooplankton ecology, e.g. increasing the risk of predation.
The study also found that increased trail volume brought about significantly enhanced total dissipated power at higher Reynolds number, and the magnitudes of total dissipated power observed varied in the range of (1.3-10)X10-9 W.
Furthermore, this study provided strong evidence that swimming speed of Daphnia and total dissipated power in Daphnia trails exceeded those of some other selected zooplankton species.
In recognizing turbulence as an intrinsic environmental perturbation in aquatic habitats, this thesis also examined the response of Daphnia to a range of turbulence flows, which correspond to turbu-lence levels that zooplankton generally encounter in their habitats. Results indicated that within the range of turbulent intensities to which the Daphnia are likely to be exposed in their natural habitats, increasing turbulence compelled the organisms to enhance their swimming activity and swim-ming speed. However, as the turbulence increased to extremely high values (10-4 m2s-3), Daphnia began to withdraw from their active swimming behaviour. Findings of this work also demonstrated that the threshold level of turbulence at which animals start to alleviate from largely active swimming is about 10-6 m2s-3. The study further illustrated that during the intermediate range of turbu-lence; 10-7 - 10-6 m2s-3, kinetic energy dissipation rates in the vicinity of the organisms is consistently one order of magnitude higher than that of the background turbulent flow.
Swarming, a common conspicuous behavioural trait observed in many zooplankton species, is considered to play a significant role in defining freshwater ecology of their habitats from food exploitation, mate encountering to avoiding predators through hydrodynamic flow structures produced by them, therefore, this thesis also investigated implications of Daphnia swarms at varied abundance & swarm densities on their swimming kinematics and induced flow field.
The results showed that Daphnia aggregated in swarms with swarm densities of (1.1-2.3)x103 L-1, which exceeded the abundance densities by two orders of magnitude (i.e. 1.7 - 6.7 L-1). The estimated swarm volume decreased from 52 cm3 to 6.5 cm3, and the mean neighbouring distance dropped from 9.9 to 6.4 body lengths. The findings of this work also showed that mean swimming trajectories were primarily horizontal concentric circles around the light source. Mean flow speeds found to be one order of magnitude lower than the corresponding swimming speeds of Daphnia. Furthermore, this study provided evidences that the flow fields produced by swarming Daphnia differed considerably between unidirectional vortex swarming and bidirectional swimming at low and high abundances respectively.