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With the emergence of current generation head-mounted displays (HMDs), virtual reality (VR) is regaining much interest in the field of medical imaging and diagnosis. Room-scale exploration of CT or MRI data in virtual reality feels like an intuitive application. However in VR retaining a high frame rate is more critical than for conventional user interaction seated in front of a screen. There is strong scientific evidence suggesting that low frame rates and high latency have a strong influence on the appearance of cybersickness. This thesis explores two practical approaches to overcome the high computational cost of volume rendering for virtual reality. One lies within the exploitation of coherency properties of the especially costly stereoscopic rendering setup. The main contribution is the development and evaluation of a novel acceleration technique for stereoscopic GPU ray casting. Additionally, an asynchronous rendering approach is pursued to minimize the amount of latency in the system. A selection of image warping techniques has been implemented and evaluated methodically, assessing the applicability for VR volume rendering.
This thesis proposes the use of MSR (Mining Software Repositories) techniques to identify software developers with exclusive expertise about specific APIs and programming domains in software repositories. A pilot Tool for finding such
“Islands of Knowledge” in Node.js projects is presented and applied in a case study to the 180 most popular npm packages. It is found that on average each package has 2.3 Islands of Knowledge, which is possibly explained by the finding that npm packages tend to have only one main contributor. In a survey, the maintainers of 50 packages are contacted and asked for opinions on the results produced by the Tool. Together with their responses, this thesis reports on experiences made with the pilot Tool and how future iterations could produce even more accurate statements about programming expertise distribution in developer teams.
In scientific data visualization huge amounts of data are generated, which implies the task of analyzing these in an efficient way. This includes the reliable detection of important parts and a low expenditure of time and effort. This is especially important for the big-sized seismic volume datasets, that are required for the exploration of oil and gas deposits. Since the generated data is complex and a manual analysis is very time-intensive, a semi-automatic approach could on one hand reduce the time required for the analysis and on the other hand offer more flexibility, than a fully automatic approach.
This master's thesis introduces an algorithm, which is capable of locating regions of interest in seismic volume data automatically by detecting anomalies in local histograms. Furthermore the results are visualized and a variety of tools for the exploration and interpretation of the detected regions are developed. The approach is evaluated by experiments with synthetic data and in interviews with domain experts on the basis of real-world data. Conclusively further improvements to integrate the algorithm into the seismic interpretation workflow are suggested.
Introduction:
In March 2012 a secessionist-Islamist insurgency gained momentum in Mali and quickly took control of two-thirds of the state territory. Within weeks radical Islamists, drug smugglers and rebels suddenly ruled over a territory bigger than Germany. News of the abuse of the population and the introduction of harsh Sharia law spread soon, and word got out that the Malian Army had simply abandoned the land. The general echo of the IC was surprise, a reaction that was, as this research will show, as unfunded as it was unconstructive*. When Malian state structures collapsed, the world watched in shock, even though the developments couldhave been anticipated –and prevented. Ultimately, the situation had to be resolved by international forces (most notably French troops), who are still in Mali at the time of writing (Arieff 2013a: 5; Lohmann 2012: 3; Walther and Christopoulos 2015: 514f.; Shaw 2013: 204; Qantara, Interview, 2012;L’Express, Mali, 2015; Deutscher Bundestag, MINUSMA und EUTM Mali, 2016; UN, MUNISMA, 2016; Boeke and Schuurmann 2015: 801; Chivvis 2016: 93f.).
This research will show that the developments in Mali in 2012 have been developing for a long time and could have been avoided. In doing so, it will also show why state security can never be analyzed or consolidated in an isolated manner. Instead, it is necessary to take into account regional dynamics and developments in order to find a comprehensive approach to security in individual states. Once state failure occurs, not only does the state itself fail, but the surrounding region equally failed to prevent the failure.
Weak states are a growing concern in many world regions, particularly in Africa. As international intervention often proves unsustainable for various reasons*, the author believes that states which cannot stabilize themselves need a regional agent to support them. This regional agent should be a Regional Security Complex (RSC) asdefined by Barry Buzan and Ole Waever (Buzan and Waever 2003). As the following analysis will show, Mali is a case in point. The hope is that this study will help avoid similar failures in the future by making a strong case for the establishment of RSC’s.
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The implementation of physiological indicators reflecting the response of organisms to changes in their environment is assumed to provide potential benefits for ecological studies. By analysing the physiological condition of organisms in freshwater ecological studies rather than their ultimate effects, physiological indicators can contribute to a faster assessment of effects than using traditional ecological indicators, such as the evaluation of the benthic community structure or the determination of the reproductive success of organisms. This can increase the effectiveness of environmental health assessment and experimental ecology. In this respect the thesis focuses on physiological measures characterizing the energetic condition and energy consumption (the concentration of energy storage compounds, the adenylate energy charge, the energy consumption in vivo), as well as individual growth (RNA:DNA ratio) of organisms. Although these sub-individual indicators are commonly applied in marine ecology and more recently in ecotoxicology, they have been rarely applied in freshwater ecology to date. With respect to an increased use of physiological indicators in freshwater ecological studies, the objectives of the present thesis are twofold. First, it highlights the potential of assessing the individual fitness by means of physiological indicators in freshwater ecological studies. For that reason, Chapter 2 provides the basic assumptions as well as the theoretical and methodological fundamentals necessary for the application of physiological indicators within freshwater ecology and, furthermore, points out their applicability by several case studies. As second objective, the thesis addresses selected ecophysiological aspects of native and non-native freshwater amphipods, which are considered suitable candidates for the determination of physiological indicators in ecological studies due to their function as keystone species within aquatic habitats. The studies presented in Chapters 3−5 of the thesis provide information on (i) species- and sex-specific seasonal variations within the energetic condition of natural Gammarus populations (G. fossarum, G. pulex), (ii) differences in metabolic activity and behaviour between different amphipod species (G fossarum, G. roeselii and D. villosus), as well as (iii) the direct effects of ambient ammonia on the physiology and behaviour of D. villosus. The fundamental conclusions drawn from the conducted field and laboratory studies, as well as their relevance and general implications for the application of physiological indicators in freshwater ecological research are discussed in Chapter 6.
This thesis explores the possibilities of probabilistic process modelling for the Computer Supported Cooperative Work (CSCW) systems in order to predict the behaviour of the users present in the CSCW system. Toward this objective applicability, advantages, limitations and challenges of probabilistic modelling are excavated in context of CSCW systems. Finally, as a primary goal seven models are created and examined to show the feasibilities of probabilistic process discovery and predictions of the users behaviour in CSCW systems.