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Statistical Shape Models (SSMs) are one of the most successful tools in 3Dimage analysis and especially medical image segmentation. By modeling the variability of a population of training shapes, the statistical information inherent in such data are used for automatic interpretation of new images. However, building a high-quality SSM requires manually generated ground truth data from clinical experts. Unfortunately, the acquisition of such data is a time-consuming, error-prone and subjective process. Due to this effort, the majority of SSMs is often based on a limited set of this ground truth training data, which makes the models less statistically meaningful. On the other hand, image data itself is abundant in clinics from daily routine. In this work, methods for automatically constructing a reliable SSM without the need of manual image interpretation from experts are proposed. Thus, the training data is assumed to be the result of any segmentation algorithm or may originate from other sources, e.g. non-expert manual delineations. Depending on the algorithm, the output segmentations will contain errors to a higher or lower degree. In order to account for these errors, areas of low probability of being a boundary should be excluded from the training of the SSM. Therefore, the probabilities are estimated with the help of image-based approaches. By including many shape variations, the corrupted parts can be statistically reconstructed. Two approaches for reconstruction are proposed - an Imputation method and Weighted Robust Principal Component Analysis (WRPCA). This allows the inclusion of many data sets from clinical routine, covering a lot more variations of shape examples. To assess the quality of the models, which are robust against erroneous training shapes, an evaluation compares the generalization and specificity ability to a model build from ground truth data. The results show, that especially WRPCA is a powerful tool to handle corrupted parts and yields to reasonable models, which have a higher quality than the initial segmentations.
This thesis is providing an overview over the current topics and influences of mobile components on Enterprise Content Management (ECM). With a literature review the core topics of enterprise mobility and ECM have been identified and projected on the context of using mobile Apps within the environment of ECM. An analysis of three ECM systems and their mobile software lead to an understanding of the functionalities and capabilities mobile systems are providing in the ECM environment. These findings lead to a better un- derstanding for the usage of mobile Enterprise Content Management and is preparation. The thesis focuses the most important topics, which need to be considered for the usage and adoption of mobile Apps in ECM.
One of the main goals of the artificial intelligence community is to create machines able to reason with dynamically changing knowledge. To achieve this goal, a multitude of different problems have to be solved, of which many have been addressed in the various sub-disciplines of artificial intelligence, like automated reasoning and machine learning. The thesis at hand focuses on the automated reasoning aspects of these problems and address two of the problems which have to be overcome to reach the afore-mentioned goal, namely 1. the fact that reasoning in logical knowledge bases is intractable and 2. the fact that applying changes to formalized knowledge can easily introduce inconsistencies, which leads to unwanted results in most scenarios.
To ease the intractability of logical reasoning, I suggest to adapt a technique called knowledge compilation, known from propositional logic, to description logic knowledge bases. The basic idea of this technique is to compile the given knowledge base into a normal form which allows to answer queries efficiently. This compilation step is very expensive but has to be performed only once and as soon as the result of this step is used to answer many queries, the expensive compilation step gets worthwhile. In the thesis at hand, I develop a normal form, called linkless normal form, suitable for knowledge compilation for description logic knowledge bases. From a computational point of view, the linkless normal form has very nice properties which are introduced in this thesis.
For the second problem, I focus on changes occurring on the instance level of description logic knowledge bases. I introduce three change operators interesting for these knowledge bases, namely deletion and insertion of assertions as well as repair of inconsistent instance bases. These change operators are defined such that in all three cases, the resulting knowledge base is ensured to be consistent and changes performed to the knowledge base are minimal. This allows us to preserve as much of the original knowledge base as possible. Furthermore, I show how these changes can be applied by using a transformation of the knowledge base.
For both issues I suggest to adapt techniques successfully used in other logics to get promising methods for description logic knowledge bases.
Science education has been facing important challenges in the recent years: the decline in student’s interest in scientific topics, and moreover, the decrease of students pursuing science beyond their compulsory studies (Bennett, Hogarth, Lubben, 2003). As a result, research has focus on examining different approaches that could attempt to improve the situation. One of these approaches has been the use of context-based problem-solving tasks (Kölbach & Sumfleth, 2011; Bennett, Hogarth, Lubben, 2003). While research into context-based problem-solving tasks suggest that they are very motivating for students, it is still unclear how they influence motivation. Following an experimental pretest-postest design, two studies examined the effects of context-based task characteristics of contextualization, complexity, and transparency, on students’ motivational variables, performance, and metacognitive experiences.
Results from both studies suggest that the task characteristic of contextualization directly influences how students’ interest is triggered and maintained throughout the task. On the other hand, the task characteristics of complexity and transparency had different effects for the other dependent variables of effort, difficulty, and solution correctness.
Moreover, data shows that other motivational variables such as anxiety and success expectancies are strongly influenced by the interaction of the parameters under study. The dissertation concludes that appropriate design and use of context-based task characteristics can benefit students’ learning processes and outcomes.
This habilitation thesis collects works addressing several challenges on handling uncertainty and inconsistency in knowledge representation. In particular, this thesis contains works which introduce quantitative uncertainty based on probability theory into abstract argumentation frameworks. The formal semantics of this extension is investigated and its application for strategic argumentation in agent dialogues is discussed. Moreover, both the computational as well as the meaningfulness of approaches to analyze inconsistencies, both in classical logics as well as logics for uncertain reasoning is investigated. Finally, this thesis addresses the implementation challenges for various kinds of knowledge representation formalisms employing any notion of inconsistency tolerance or uncertainty.
Agriculture covers one third of the world land area and has become a major source of water pollution due to its heavy reliance on chemical inputs, namely fertilisers and pesticides. Several thousands of tonnes of these chemicals are applied worldwide annually and partly reach freshwaters. Despite their widespread use and relatively unspecific modes of action, fungicides are the least studied group of pesticides. It remains unclear whether the taxonomic groups used in pesticide risk assessment are protective for non-target freshwater fungi. Fungi and bacteria are the main microbial decomposers converting allochthonous organic matter (litter) into a more nutritious food resource for leaf-shredding macroinvertebrates. This process of litter decomposition (LD) is central for aquatic ecosystem because it fuels local and downstream food webs with energy and nutrients. Effects of fungicides on decomposer communities and LD have been mainly analysed under laboratory conditions with limited representation of the multiple factors that may moderate effects in the field.
In this thesis a field study was conducted in a German vineyard area to characterise recurrent episodic exposure to fungicides in agricultural streams (chapter 2) and its effects on decomposer communities and LD (chapter 3). Additionally, potential interaction effects of nutrient enrichment and fungicides on decomposer communities and LD were analysed in a mesocosm experiment (chapter 4).
In the field study event-driven water sampling (EDS) and passive sampling with EmporeTM styrene-divinylbenzene reverse phase sulfonated disks (SDB disks) were used to assess exposure to 15 fungicides and 4 insecticides. A total of 17 streams were monitored during 4 rainfall events within the local application period of fungicides in 2012. EDS exceeded the time-weighted average concentrations provided by the SDB disks by a factor of 3, though high variability among compounds was observed. Most compounds were detected in more than half of the sites and mean and maximum peak (EDS) concentrations were under 1 and 3 µg/l, respectively. Besides, SDB disk-sampling rates and a free-software solution to derive sampling rates under time-variable exposure were provided.
Several biotic endpoints related to decomposers and LD were measured in the same sampling sites as the fungicide monitoring, coinciding with the major litter input period. Our results suggest that polar organic fungicides in streams change the structure of the fungal community. Causality of this finding was supported by a subsequent microcosm experiment. Whether other effects observed in the field study, such as reduced fungal biomass, increased bacterial density or reduced microbial LD can be attributed to fungicides remains speculative and requires further investigation. By contrast, neither the invertebrate LD nor in-situ measured gammarid feeding rates correlated with water-borne fungicide toxicity, but both were negatively associated with sediment copper concentrations. The mesocosm experiment showed that fungicides and nutrients affect microbial decomposers differently and that they can alter community structure, though longer experiments are needed to determine whether these changes may propagate to invertebrate communities and LD. Overall, further studies should include representative field surveys in terms of fungicide pollution and physical, chemical and biological conditions. This should be combined with experiments under controlled conditions to test for the causality of field observations.
Six and Gimmler have identified concrete capabilities that enable users to use the Internet in a competent way. Their media competence model can be used for the didactical design of media usage in secondary schools. However, the special challenge of security awareness is not addressed by the model. In this paper, the important dimension of risk and risk assessment will be introduced into the model. This is especially relevant for the risk of the protection of personal data and privacy. This paper will apply the method of IT risk analysis in order to select those dimensions of the Six/Gimmler media competence model that are appropriate to describe privacy aware Internet usage. Privacy risk aware decisions for or against the Internet usage is made visible by the trust model of Mayer et al.. The privacy extension of the competence model will lead to a measurement of the existing privacy awareness in secondary schools, which, in turn, can serve as a didactically well-reasoned design of Informatics modules in secondary schools. This paper will provide the privacy-extended competence model, while empirical measurement and module design is planned for further research activities.
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.
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.
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.
Reactive local algorithms are distributed algorithms which suit the needs of battery-powered, large-scale wireless ad hoc and sensor networks particularly well. By avoiding both unnecessary wireless transmissions and proactive maintenance of neighborhood tables (i.e., beaconing), such algorithms minimize communication load and overhead, and scale well with increasing network size. This way, resources such as bandwidth and energy are saved, and the probability of message collisions is reduced, which leads to an increase in the packet reception ratio and a decrease of latencies.
Currently, the two main application areas of this algorithm type are geographic routing and topology control, in particular the construction of a node's adjacency in a connected, planar representation of the network graph. Geographic routing enables wireless multi-hop communication in the absence of any network infrastructure, based on geographic node positions. The construction of planar topologies is a requirement for efficient, local solutions for a variety of algorithmic problems.
This thesis contributes to reactive algorithm research in two ways, on an abstract level, as well as by the introduction of novel algorithms:
For the very first time, reactive algorithms are considered as a whole and as an individual research area. A comprehensive survey of the literature is given which lists and classifies known algorithms, techniques, and application domains. Moreover, the mathematical concept of O- and Omega-reactive local topology control is introduced. This concept unambiguously distinguishes reactive from conventional, beacon-based, topology control algorithms, serves as a taxonomy for existing and prospective algorithms of this kind, and facilitates in-depth investigations of the principal power of the reactive approach, beyond analysis of concrete algorithms.
Novel reactive local topology control and geographic routing algorithms are introduced under both the unit disk and quasi unit disk graph model. These algorithms compute a node's local view on connected, planar, constant stretch Euclidean and topological spanners of the underlying network graph and route messages reactively on these spanners while guaranteeing the messages' delivery. All previously known algorithms are either not reactive, or do not provide constant Euclidean and topological stretch properties. A particularly important partial result of this work is that the partial Delaunay triangulation (PDT) is a constant stretch Euclidean spanner for the unit disk graph.
To conclude, this thesis provides a basis for structured and substantial research in this field and shows the reactive approach to be a powerful tool for algorithm design in wireless ad hoc and sensor networking.
During olive oil production, large amounts of olive mill wastewater (OMW) are generated within a short period of time. OMW has a high nutrient content and could serve as fertilizer when applied on land. However, its fatty and phenolic constituents have adverse effects on soil properties. It is still unknown how seasonal fluctuations in temperature and precipitation influence the fate and effect of OMW components on soil properties in a long-term perspective. An appropriate application season could mitigate negative consequences of OMW while preserving its beneficial effects. In order to investigate this, 14 L OMW m-2 were applied to different plots of an olive plantation in winter, spring, and summer respectively. Hydrological soil properties (water drop penetration time, hydraulic conductivity, dynamic contact angle), physicochemical parameters (pH, EC, soluble ions, phenolic compounds, organic matter), and biological degradation (bait-lamina test) were measured to assess the soil state after OMW application. After one rainy season following OMW application, the soil quality of summer treatments significantly decreased compared to the control. This was particularly apparent in a three-times lower biodegradation performance, ten-fold higher soil water repellency, and a four-fold higher content of phenolic compounds. The soil properties of winter treatments were comparable to the control, which demonstrated the recovery potential of the soil ecosystem. Spring treatments resulted in an intermediate response compared to summer and winter treatments, but without any precipitation following OMW application. Significant accumulation or leaching effects to deeper soil were not observed. Therefore, the direct application of legally restricted OMW amounts to soil is considered acceptable during the moist seasons. Further research is needed to quantify the effect of spring treatments and to gain further insight into the composition and kinetics of organic OMW constituents in the soil.
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 global problematic issue of the olive oil industry is in its generation of large amounts of olive mill wastewater (OMW). The direct discharge of OMW to the soil is very common which presents environmental problems for olive oil producing countries. Both, positive as well as negative effects on soil have been found in earlier studies. Therefore, the current study hypothesized that whether beneficial effects or negative effects dominate depends on the prevailing conditions before and after OMW discharge to soil. As such, a better understanding of the OMW-soil interaction mechanisms becomes essential for sustainable safe disposal of OMW on soil and sustainable soil quality.
A field experiment was carried out in an olive orchard in Palestine, over a period of 24 months, in which the OMW was applied to the soil as a single application of 14 L m-2 under four different environmental conditions: in winter (WI), spring (SP), and summer with and without irrigation (SUmoist and SUdry). The current study investigated the effects of seasonal conditions on the olive mill wastewater (OMW) soil interaction in the short-term and the long-term. The degree and persistence of soil salinization, acidification, accumulation of phenolic compounds and soil water repellency were investigated as a function of soil depth and time elapsed after the OMW application. Moreover, the OMW impacts on soil organic matter SOM quality and quantity, total organic carbon (SOC), water-extractable soil organic carbon (DOC), as well as specific ultraviolet absorbance analysis (SUVA254) were also investigated for each seasonal application in order to assess the degree of OMW-OM decomposition or accumulation in soil, and therefore, the persisting effects of OMW disposal to soil.
The results of the current study demonstrate that the degree and persistence of relevant effects due to OMW application on soil varied significantly between the different seasonal OMW applications both in the short-term and the long-term. The negative effects of the potentially hazardous OMW residuals in the soil were highly dependent on the dominant transport mechanisms and transformation mechanisms, triggered by the ambient soil moisture and temperature which either intensified or diminished negative effects of OMW in the soil during and after the application season. The negative effects of OMW disposal to the soil decreased by increasing the retention time of OMW in soil under conditions favoring biological activity. The moderate conditions of soil moisture and temperature allowed for a considerable amount of applied OMW to be biologically degraded, while the prolonged application time under dry conditions and high temperature resulted in a less degradable organic fraction of the OMW, causing the OMW constituents to accumulate and polymerize without being degraded. Further, the rainfall during winter season diminished negative effects of OMW in the soil; therefore, the risk of groundwater contamination by non-degraded constituents of OMW can be highly probable during the winter season.
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.
In order to enhance the company’s appeal for potential employees and improve the satisfaction of already salaried workers, it is necessary to offer a variety of work-life balance measures. But as their implementation causes time and financial costs, a prioritization of measures is needed. To express a recommendation for companies, this study is led by the questions if there are work-life balance measures which have more impact on employee satisfaction than others, how big the relative impact of work-life balance measures on job satisfaction in comparison to other work and private life variables is, if there is a relation between the effectiveness of measures and their use and if there is a difference between the measures which are most important from the employees’ perspective and the companies’ offers.
These questions are formulated in eight research hypotheses which are examined in a quantitative research design with online survey data from 289 employees of fifteen different German companies. The formation of a hierarchy of the effectiveness of measures towards job satisfaction as well as the investigation of the relative impact in comparison to other variables is performed using a multiple regression analysis, whilst the differences between employees’ expectations and the availability of offers are examined with t-tests.
Support in childcare, support in voluntary activities and teambuilding events have a significantly higher impact on job satisfaction than other work-life balance measures, and their potential use is higher than the actual use which leads to the conclusion that there is yet potential for companies to improve their employees’ satisfaction by implementing these measures. In addition, flexible work hours, flexible work locations and free time and overtime accounts are the most important measures from the employees’ point of view and already widely offered by the surveyed companies. In general, the overall use of the available measures and the quantity of offered measures are more important with regard to job satisfaction than the specific kind of measure. In addition, work-life balance measures are more important towards job satisfaction for younger people.
How entrepreneurs become successful with their business ideas has been a topic of discussion within entrepreneurial research circles for many years. Business success has been related to psychological characteristics and many research findings have explained how people become entrepreneurs and furthermore, how they find success in regards to their business ventures. People always wanted to know what defines an entrepreneur and more importantly, what is needed to become a successful entrepreneur. Curious minds began to search for the recipe for success. Personality Traits have been researched for years, leading to the discovery of many diverse and distinct forms which are still recognized today. Researchers compared the Behavioral Approach or the analysis of demographical characteristics to success.
This raises the question of what an entrepreneur needs to become successful which is made more difficult due to the fact that entrepreneurship and who an entrepreneur is can be difficult do define exactly. Entrepreneurs are diverse and distinct individuals that each possess their own characteristics, behavior and reasons for starting a business. Many people assume that it is just someone who starts their own business. While partially correct, this only scratches the surface of what it is to be an entrepreneur.
This thesis answers the following three research questions: 1. Which personality traits were found in the almost sixty years of researching? 2. What triggers do entrepreneurs need for starting a new business? 3. Which factor makes the entrepreneur successful with their business idea? Also, reading the thesis, one may gain a better understanding of what entrepreneurship is, what defines an entrepreneur and what one needs to become a successful entrepreneur.
In this thesis the reviewing literature method developed by Wolfswinkel et al. (2011) was used to identify suitable literature and references for the main chapters. For that the five stages of the grounded-theory method for reviewing the literature were used in an iterative fashion. In step one inclusion and exclusion criterias for literature were defined. Then literature was searched matching the criterias of step one. In step three the samples were refined. Then in step four the found literature was analyzed and coded before the results of this research was presented in the following text. Many entrepreneurial personality traits were discovered and confirmed during the studies conducted over the last sixty years, these include but are not limited to Need for Achievement, Locus of Control, or risk taking propensity. Motivation is clearly the main trigger to start your own business. During the studies reasons were discovered of how and why an entrepreneur may become successful outside of posessing the right combination of traits. For example: having human, financial and social capital, an entrepreneurial behavior and the right economic conditions to start a business that will survive for more than five years.
Leaf litter breakdown is a fundamental process in aquatic ecosystems, being mainly mediated by decomposer-detritivore systems that are composed of microbial decomposers and leaf-shredding, detritivorous invertebrates. The ecological integrity of these systems can, however, be disturbed, amongst others, by chemical stressors. Fungicides might pose a particular risk as they can have negative effects on the involved microbial decomposers but may also affect shredders via both waterborne toxicity and their diet; the latter by toxic effects due to dietary exposure as a result of fungicides’ accumulation on leaf material and by negatively affecting fungal leaf decomposers, on which shredders’ nutrition heavily relies. The primary aim of this thesis was therefore to provide an in-depth assessment of the ecotoxicological implications of fungicides in a model decomposer-detritivore system using a tiered experimental approach to investigate (1) waterborne toxicity in a model shredder, i.e., Gammarus fossarum, (2) structural and functional implications in leaf-associated microbial communities, and (3) the relative importance of waterborne and diet-related effects for the model shredder.
Additionally, knowledge gaps were tackled that were related to potential differences in the ecotoxicological impact of inorganic (also authorized for organic farming in large parts of the world) and organic fungicides, the mixture toxicity of these substances, the field-relevance of their effects, and the appropriateness of current environmental risk assessment (ERA).
In the course of this thesis, major differences in the effects of inorganic and organic fungicides on the model decomposer-detritivore system were uncovered; e.g., the palatability of leaves for G. fossarum was increased by inorganic fungicides but deteriorated by organic substances. Furthermore, non-additive action of fungicides was observed, rendering mixture effects of these substances hardly predictable. While the relative importance of the waterborne and diet-related effect pathway for the model shredder seems to depend on the fungicide group and the exposure concentration, it was demonstrated that neither path must be ignored due to additive action. Finally, it was shown that effects can be expected at field-relevant fungicide levels and that current ERA may provide insufficient protection for decomposer-detritivore systems. To safeguard aquatic ecosystem functioning, this thesis thus recommends including leaf-associated microbial communities and long-term feeding studies using detritus feeders in ERA testing schemes, and identifies several knowledge gaps whose filling seems mandatory to develop further reasonable refinements for fungicide ERA.
“Did I say something wrong?” A word-level analysis of Wikipedia articles for deletion discussions
(2016)
This thesis focuses on gaining linguistic insights into textual discussions on a word level. It was of special interest to distinguish messages that constructively contribute to a discussion from those that are detrimental to them. Thereby, we wanted to determine whether “I”- and “You”-messages are indicators for either of the two discussion styles. These messages are nowadays often used in guidelines for successful communication. Although their effects have been successfully evaluated multiple times, a large-scale analysis has never been conducted. Thus, we used Wikipedia Articles for Deletion (short: AfD) discussions together with the records of blocked users and developed a fully automated creation of an annotated data set. In this data set, messages were labelled either constructive or disruptive. We applied binary classifiers to the data to determine characteristic words for both discussion styles. Thereby, we also investigated whether function words like pronouns and conjunctions play an important role in distinguishing the two. We found that “You”-messages were a strong indicator for disruptive messages which matches their attributed effects on communication. However, we found “I”-messages to be indicative for disruptive messages as well which is contrary to their attributed effects. The importance of function words could neither be confirmed nor refuted. Other characteristic words for either communication style were not found. Yet, the results suggest that a different model might represent disruptive and constructive messages in textual discussions better.
Confidentiality, integrity, and availability are often listed as the three major requirements for achieving data security and are collectively referred to as the C-I-A triad. Confidentiality of data restricts the data access to authorized parties only, integrity means that the data can only be modified by authorized parties, and availability states that the data must always be accessible when requested. Although these requirements are relevant for any computer system, they are especially important in open and distributed networks. Such networks are able to store large amounts of data without having a single entity in control of ensuring the data's security. The Semantic Web applies to these characteristics as well as it aims at creating a global and decentralized network of machine-readable data. Ensuring the confidentiality, integrity, and availability of this data is therefore also important and must be achieved by corresponding security mechanisms. However, the current reference architecture of the Semantic Web does not define any particular security mechanism yet which implements these requirements. Instead, it only contains a rather abstract representation of security.
This thesis fills this gap by introducing three different security mechanisms for each of the identified security requirements confidentiality, integrity, and availability of Semantic Web data. The mechanisms are not restricted to the very basics of implementing each of the requirements and provide additional features as well. Confidentiality is usually achieved with data encryption. This thesis not only provides an approach for encrypting Semantic Web data, it also allows to search in the resulting ciphertext data without decrypting it first. Integrity of data is typically implemented with digital signatures. Instead of defining a single signature algorithm, this thesis defines a formal framework for signing arbitrary Semantic Web graphs which can be configured with various algorithms to achieve different features. Availability is generally supported by redundant data storage. This thesis expands the classical definition of availability to compliant availability which means that data must only be available as long as the access request complies with a set of predefined policies. This requirement is implemented with a modular and extensible policy language for regulating information flow control. This thesis presents each of these three security mechanisms in detail, evaluates them against a set of requirements, and compares them with the state of the art and related work.