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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.
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.
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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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.
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.
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.
Part-of-Speech tagging is the process of assigning words with similar grammatical properties to a part of speech (PoS). In the English language, PoS-tagging algorithms generally reach very high accuracy. This thesis undertakes the task to test against these accuracies in PoS-tagging as a qualitative measure in classification capabilities for a recently developed neural network model, called graph convolutional network (GCN). The novelty proposed in this thesis is to translate a corpus into a graph as a direct input for the GCN. The experiments in this thesis serve as a proof of concept with room for improvements.
The Web contains some extremely valuable information; however, often poor quality, inaccurate, irrelevant or fraudulent information can also be found. With the increasing amount of data available, it is becoming more and more difficult to distinguish truth from speculation on the Web. One of the most, if not the most, important criterion used to evaluate data credibility is the information source, i.e., the data origin. Trust in the information source is a valuable currency users have to evaluate such data. Data popularity, recency (or the time of validity), reliability, or vagueness ascribed to the data may also help users to judge the validity and appropriateness of information sources. We call this knowledge derived from the data the provenance of the data. Provenance is an important aspect of the Web. It is essential in identifying the suitability, veracity, and reliability of information, and in deciding whether information is to be trusted, reused, or even integrated with other information sources. Therefore, models and frameworks for representing, managing, and using provenance in the realm of Semantic Web technologies and applications are critically required. This thesis highlights the benefits of the use of provenance in different Web applications and scenarios. In particular, it presents management frameworks for querying and reasoning in the Semantic Web with provenance, and presents a collection of Semantic Web tools that explore provenance information when ranking and updating caches of Web data. To begin, this thesis discusses a highly exible and generic approach to the treatment of provenance when querying RDF datasets. The approach re-uses existing RDF modeling possibilities in order to represent provenance. It extends SPARQL query processing in such a way that given a SPARQL query for data, one may request provenance without modifying it. The use of provenance within SPARQL queries helps users to understand how RDF facts arederived, i.e., it describes the data and the operations used to produce the derived facts. Turning to more expressive Semantic Web data models, an optimized algorithm for reasoning and debugging OWL ontologies with provenance is presented. Typical reasoning tasks over an expressive Description Logic (e.g., using tableau methods to perform consistency checking, instance checking, satisfiability checking, and so on) are in the worst case doubly exponential, and in practice are often likewise very expensive. With the algorithm described in this thesis, however, one can efficiently reason in OWL ontologies with provenance, i.e., provenance is efficiently combined and propagated within the reasoning process. Users can use the derived provenance information to judge the reliability of inferences and to find errors in the ontology. Next, this thesis tackles the problem of providing to Web users the right content at the right time. The challenge is to efficiently rank a stream of messages based on user preferences. Provenance is used to represent preferences, i.e., the user defines his preferences over the messages' popularity, recency, etc. This information is then aggregated to obtain a joint ranking. The aggregation problem is related to the problem of preference aggregation in Social Choice Theory. The traditional problem formulation of preference aggregation assumes a I fixed set of preference orders and a fixed set of domain elements (e.g. messages). This work, however, investigates how an aggregated preference order has to be updated when the domain is dynamic, i.e., the aggregation approach ranks messages 'on the y' as the message passes through the system. Consequently, this thesis presents computational approaches for online preference aggregation that handle the dynamic setting more efficiently than standard ones. Lastly, this thesis addresses the scenario of caching data from the Linked Open Data (LOD) cloud. Data on the LOD cloud changes frequently and applications relying on that data - by pre-fetching data from the Web and storing local copies of it in a cache - need to continually update their caches. In order to make best use of the resources (e.g., network bandwidth for fetching data, and computation time) available, it is vital to choose a good strategy to know when to fetch data from which data source. A strategy to cope with data changes is to check for provenance. Provenance information delivered by LOD sources can denote when the resource on the Web has been changed last. Linked Data applications can benefit from this piece of information since simply checking on it may help users decide which sources need to be updated. For this purpose, this work describes an investigation of the availability and reliability of provenance information in the Linked Data sources. Another strategy for capturing data changes is to exploit provenance in a time-dependent function. Such a function should measure the frequency of the changes of LOD sources. This work describes, therefore, an approach to the analysis of data dynamics, i.e., the analysis of the change behavior of Linked Data sources over time, followed by the investigation of different scheduling update strategies to keep local LOD caches up-to-date. This thesis aims to prove the importance and benefits of the use of provenance in different Web applications and scenarios. The exibility of the approaches presented, combined with their high scalability, make this thesis a possible building block for the Semantic Web proof layer cake - the layer of provenance knowledge.
With global and distributed project teams being increasingly common Collaborative Project Management is becoming the prevalent paradigm for the work in most organisations. Software has for many years been one of the most used tools for supporting Project Management and with the focus on Collaborative Project Management and accompanied by the emergence of Enterprise Collaboration Systems (ECS), Collaborative Project Management Software (CPMS) is gaining increased attention. This thesis examines the capabilities of CPMS for the long-term management of information which not only includes the management of files within these systems, but the management of all types of digital business documents, particularly social business documents. Previous research shows that social content in collaboration software is often poorly managed which poses challenges to meeting performance and conformance objectives in a business. Based on literature research, requirements for the long-term management of information in CPMS are defined and 7 CPMS tools are analysed regarding the content they contain and the functionalities for the long-term management of this content they offer. The study shows that CPMS by and large are not able to meet the long-term information management needs of an organisation on their own and that only the tools geared towards enterprise customers have sufficient capabilities to support the implementation of an Enterprise Information Management strategy.
Using semantic data from general-purpose programming languages does not provide the unified experience one would want for such an application. Static error checking is lacking, especially with regards to static typing of the data. Based on the previous work of λ-DL, which integrates semantic queries and concepts as types into a typed λ-calculus, this work takes its ideas a step further to meld them into a real-world programming language. This thesis explores how λ-DL's features can be extended and integrated into an existing language, researches an appropriate extension mechanism and produces Semantics4J, a JastAdd-based Java language semantic data extension for type-safe OWL programming, together with examples of its usage.