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The mitral valve is one of four human heart valves. It is located in the left heart and acts as a unidirectional passageway for blood between the left atrium and the left ventricle. A correctly functioning mitral valve prevents a backflow of blood into the pulmonary circulation (lungs) and thus constitutes a vital part of the cardiac cycle. Pathologies of the mitral valve can manifest in a variety of symptoms with severity ranging from chest pain and fatigue to pulmonary edema (fluid accumulation in the tissue and air space of lungs), which may ultimately cause respiratory failure.
Malfunctioning mitral valves can be restored through complex surgical interventions, which greatly benefit from intensive planning and pre-operative analysis. Visualization techniques provide a possibility to enhance such preparation processes and can also facilitate post-operative evaluation. The work at hand extends current research in this field, building upon patient-specific mitral valve segmentations developed at the German Cancer Research Center, which result in triangulated 3D models of the valve surface. The core of this work will be the construction of a 2D-view of these models through global parameterization, a method that can be used to establish a bijective mapping between a planar parameter domain and a surface embedded in higher dimensions.
A flat representation of the mitral valve provides physicians with a view of the whole surface at once, similar to a map. This allows assessment of the valve's area and shape without the need for different viewing angles. Parts of the valve that are occluded by geometry in 3D become visible in 2D.
An additional contribution of this work will be the exploration of different visualizations of the 3D and 2D mitral valve representations. Features of the valve can be highlighted by associating them with specified colors, which can for instance directly convey pathology indicators.
Quality and effectiveness of the proposed methods were evaluated through a survey conducted at the Heidelberg University Hospital.
This thesis deals with the verbal categories tense and aspect in the context of analysing the English perfect. The underlying notion of time is examined from the viewpoint of etymology and from the viewpoint of fields of knowledge that lie outside the immediate scope of temporal semantics, e.g. mathematics. The category tense is scrutinised by discussing the concept of Reichenbach tense and the concept of correlation (Giering). The starting point of the discussion of the category verbal aspect is the dichotomy perfective vs. imperfective in the Slavic languages. The main part about the perfect is concerned with the possessive perfect as a cross-linguistic phenomenon (including a comparison of the English and the Slavic perfect) and focuses on the usage and the meaning of the English present perfect. There are three appendices which are an integral part of this dissertation. Appendix A deals with the systematization of English verb forms and their graphical representation. Three different visualizations are presented, two of which are genuine to this paper. Appendix B reproduces the target setting according to which an animated visualization of English infinitives was programmed. Appendix C represents a synopsis of approaches to the English perfect in grammars and textbooks.
Social networks are ubiquitous structures that we generate and enrich every-day while connecting with people through social media platforms, emails, and any other type of interaction. While these structures are intangible to us, they carry important information. For instance, the political leaning of our friends can be a proxy to identify our own political preferences. Similarly, the credit score of our friends can be decisive in the approval or rejection of our own loans. This explanatory power is being leveraged in public policy, business decision-making and scientific research because it helps machine learning techniques to make accurate predictions. However, these generalizations often benefit the majority of people who shape the general structure of the network, and put in disadvantage under-represented groups by limiting their resources and opportunities. Therefore it is crucial to first understand how social networks form to then verify to what extent their mechanisms of edge formation contribute to reinforce social inequalities in machine learning algorithms.
To this end, in the first part of this thesis, I propose HopRank and Janus two methods to characterize the mechanisms of edge formation in real-world undirected social networks. HopRank is a model of information foraging on networks. Its key component is a biased random walker based on transition probabilities between k-hop neighborhoods. Janus is a Bayesian framework that allows to identify and rank plausible hypotheses of edge formation in cases where nodes possess additional information. In the second part of this thesis, I investigate the implications of these mechanisms - that explain edge formation in social networks - on machine learning. Specifically, I study the influence of homophily, preferential attachment, edge density, fraction of inorities, and the directionality of links on both performance and bias of collective classification, and on the visibility of minorities in top-k ranks. My findings demonstrate a strong correlation between network structure and machine learning outcomes. This suggests that systematic discrimination against certain people can be: (i) anticipated by the type of network, and (ii) mitigated by connecting strategically in the network.
Systemic neonicotinoids are one of the most widely used insecticide classes worldwide. In addition to their use in agriculture, they are increasingly applied on forest trees as a protective measure against insect pests. However, senescent leaves containing neonicotinoids might, inter alia during autumn leaf fall, enter nearby streams. There, the hydrophilic neonicotinoids may be remobilized from leaves to water resulting in waterborne exposure of aquatic non-target organisms. Despite the insensitivity of the standard test species Daphnia magna (Crustacea, Cladocera) toward neonicotinoids, a potential risk for aquatic organisms is evident as many other aquatic invertebrates (in particular insects and amphipods) display adverse effects when exposed to neonicotinoids in the ng/L- to low µg/L-range. In addition to waterborne exposure, in particular leaf-shredding invertebrates (= shredders) might be adversely affected by the introduction of neonicotinoid-contaminated leaves into the aquatic environment since they heavily rely on leaf litter as food source. However, dietary neonicotinoid exposure of aquatic shredders has hardly received any attention from researchers and is not considered during aquatic environmental risk assessment. The primary aim of this thesis is, therefore, (1) to characterize foliar neonicotinoid residues and exposure pathways relevant for aquatic shredders, (2) to investigate ecotoxicological effects of waterborne and dietary exposure on two model shredders, namely Gammarus fossarum (Crustacea, Amphipoda) and Chaetopteryx villosa (Insecta, Trichoptera), and (3) to identify biotic and abiotic factors potentially modulating exposure under field conditions.
During the course of this thesis, ecotoxicologically relevant foliar residues of the neonicotinoids imidacloprid, thiacloprid and acetamiprid were quantified in black alder trees treated at field relevant levels. A worst-case model – developed to simulate imidacloprid water concentrations resulting from an input of contaminated leaves into a stream – predicted only low aqueous imidacloprid concentrations (i.e., ng/L-range). However, the model identified dietary uptake as an additional exposure pathway relevant for shredders up to a few days after the leaves’ introduction into the stream. When test organisms were simultaneously exposed (= combined exposure) to neonicotinoids leaching from leaves into the water and via the consumption of contaminated leaves, adverse effects exceeded those observed under waterborne exposure alone. When exposure pathways were separated using a flow-through system, dietary exposure towards thiacloprid-contaminated leaves caused similar sublethal adverse effects in G. fossarum as observed under waterborne exposure. Moreover, the effect sizes observed under combined exposure were largely predictable using the reference model “independent action”, which assumes different molecular target sites to be affected. Dietary toxicity for shredders might, however, be reduced under field conditions since UV-induced photodegradation and leaching decreased imidacloprid residues in leaves and thereby the toxicity for G. fossarum. In contrast, both shredders were found unable to actively avoid dietary exposure. This thesis thus recommends considering dietary exposure towards systemic insecticides, such as neonicotinoids, already during their registration to safeguard aquatic shredders, associated ecosystem functions (e.g., leaf litter breakdown) and ultimately ecosystem integrity.
Colonoscopy is the gold standard for the detection of colorectal polyps that can progress into cancer. In such an examination, physicians search for polyps in endoscopic images. Thereby polyps can be removed. To support experts with a computer-aided diagnosis system, the University of Koblenz-Landau currently makes some efforts in research different methods for automatic detection. Comparable to traditional pattern recognition systems, features are initially extracted and a classifier is trained on such data. Afterwards, unknown endoscopic images can be classified with the previously trained classifier. This thesis concentrates on the extension of the feature extraction module in the existing system. New detection methods are compared to existing techniques. Several features are implemented, incorporating Graylevel Co-occurrence Matrices, Local Binary Patterns and Discrte Wavelet Transform. Different modifications on those features are applied and evaaluated.
Magnetic resonance (MR) tomography is an imaging method, that is used to expose the structure and function of tissues and organs in the human body for medical diagnosis. Diffusion weighted (DW) imaging is a specific MR imaging technique, which enables us to gain insight into the connectivity of white matter pathways noninvasively and in vivo. It allows for making predictions about the structure and integrity of those connections. In clinical routine this modality finds application in the planning phase of neurosurgical operations, such as in tumor resections. This is especially helpful if the lesion is deeply seated in a functionally important area, where the risk of damage is given. This work reviews the concepts of MR imaging and DW imaging. Generally, at the current resolution of diffusion weighted data, single white matter axons cannot be resolved. The captured signal rather describes whole fiber bundles. Beside this, it often appears that different complex fiber configurations occur in a single voxel, such as crossings, splittings and fannings. For this reason, the main goal is to assist tractography algorithms who are often confound in such complex regions. Tractography is a method which uses local information to reconstruct global connectivities, i.e. fiber tracts. In the course of this thesis, existing reconstruction methods such as diffusion tensor imaging (DTI) and q-ball imaging (QBI) are evaluated on synthetic generated data and real human brain data, whereas the amount of valuable information provided by the individual reconstruction mehods and their corresponding limitations are investigated. The output of QBI is the orientation distribution function (ODF), where the local maxima coincides with the underlying fiber architecture. We determine those local maxima. Furthermore, we propose a new voxel-based classification scheme conducted on diffusion tensor metrics. The main contribution of this work is the combination of voxel-based classification, local maxima from the ODF and global information from a voxel- neighborhood, which leads to the development of a global classifier. This classifier validates the detected ODF maxima and enhances them with neighborhood information. Hence, specific asymmetric fibrous architectures can be determined. The outcome of the global classifier are potential tracking directions. Subsequently, a fiber tractography algorithm is designed that integrates along the potential tracking directions and is able to reproduce splitting fiber tracts.
Recent EU-frameworks enforce the implementation of risk mitigation measures for nonpoint-source pesticide pollution in surface waters. Vegetated surface flow treatments systems (VTS) can be a way to mitigate risk of adverse effects in the aquatic ecosystems following unavoidable pollution after rainfall-related runoff events. Studies in experimental wetland cells and vegetated ditch mesocosms with common fungicides, herbicides and insecticides were performed to assess efficiency of VTS. Comprehensive monitoring of fungicide exposure after rainfall-related runoff events and reduction of pesticide concentrations within partially optimised VTS was performed from 2006-2009 at five vegetated detention ponds and two vegetated ditches in the wine growing region of the Southern Palatinate (SW-Germany).
Influence of plant density, size related parameters and pesticide properties in the performance of the experimental devices, and the monitored systems were the focus of the analysis. A spatial tool for prediction of pesticide pollution of surface waters after rainfall-related runoff events was programmed in a geographic information system (GIS). A sophisticated and high resolution database on European scale was built for simulation. With the results of the experiments, the monitoring campaign and further results of the EU-Life Project ArtWET mitigation measures were implemented in a georeferenced spatial decision support system. The database for the GIS tools was built with open data. The REXTOX (ratio of exposure to toxicity) Risk Indicator, which was proposed by the OECD (Organisation for Economic Co-operation and Development), was extended, and used for modeling the risk of rainfall-related runoff exposure to pesticides, for all agricultural waterbodies on European scale. Results show good performance of VTS. The vegetated ditches and wetland cells of the experimental systems showed a very high reduction of more than 90% of pesticide concentrations and potential adverse effects. Vegetated ditches and wetland cells performed significantly better than devices without vegetation. Plant density and sorptivity of the pesticide were the variables with the highest explanatory power regarding the response variable reduction of concentrations. In the experimental vegetated ditches 65% of the reduction of peak concentrations was explained with plant density and KOC. The monitoring campaign showed that concentrations of the fungicides and potential adverse effects of the mixtures were reduced significantly within vegetated ditches (Median 56%) and detention ponds (Median 38%) systems. Regression analysis with data from the monitoring campaign identified plant density and size related properties as explanatory variables for mitigation efficiency (DP: R²=0.57, p<0.001; VD:
R²=0.19, p<0.001). Results of risk model runs are the input for the second tool, simulating three risk mitigation measures. VTS as risk mitigation measures are implemented using the results for plant density and size related performance of the experimental and monitoring studies, supported by additional data from the ArtWET project. Based on the risk tool, simulations can be performed for single crops, selected regions, different pesticide compounds and rainfall events. Costs for implementation of the mitigation measures are estimated. Experiments and monitoring, with focus on the whole range of pesticides, provide novel information on VTS for pesticide pollution. The monitoring campaign also shows that fungicide pollution may affect surface waters. Tools developed for this study are easy to use and are not only a good base for further spatial analysis but are also useful as decision support of the non-scientific community. On a large scale, the tools on the one hand can help to compute external costs of pesticide use with simulation of mitigation costs on three levels, on the other hand feasible measures mitigating or remediating the effects of nonpoint-source pollution can be identified for implementation. Further study of risk of adverse effects caused by fungicide pollution and long-time performance of optimised VTS is needed.
The status of Business Process Management (BPM) recommender systems is not quite clear as research states. The use of recommenders familiarized itself with the world during the rise of technological evolution in the past decade.Ever since then, several BPM recommender systems came about. However, not a lot of research is conducted in this field. It is not well known to what broad are the technologies used and how are they used. Moreover, this master’s thesis aims at surveying the BPM recommender systems existing. Building on this, the recommendations come in different shapes. They can be positionbased where an element is to be placed at an element’s front, back or to autocomplete a missing link. On the other hand, Recommendations can be textual, to fill the labels of the elements. Furthermore, the literature review for BPM recommender systems took place under the guides of a literature review framework. The framework suggests 5stages of consecutive stages for this sake. The first stage is defining a scope for the research. Secondly, conceptualizing the topic by choosing key terms for literature research. After that in the third stage, comes the research stage.As for the fourth stage, it suggests choosing analysis features over which the literature is to be synthesized and compared. Finally, it recommends defining the research agenda to describe the reason for the literature review. By invoking the mentioned methodology, this master’s thesis surveyed 18 BPM recommender systems. It was found as a result of the survey that there
are not many different technologies for implementing the recommenders. It was also found that the majority of the recommenders suggest nodes that are yet to come in the model, which is called forward recommending. Also, one of the results of the survey indicated the scarce use of textual recommendations to BPM labels. Finally, 18 recommenders are considered less than excepted for a developing field therefore as a result, the survey found a shortage in the number of BPM recommender systems. The results indicate several shortages in several aspects in the field of BPM recommender systems. On this basis, this master’s thesis recommends the future work on it the results.
Expert-driven business process management is an established means for improving efficiency of organizational knowledge work. Implicit procedural knowledge in the organization is made explicit by defining processes. This approach is not applicable to individual knowledge work due to its high complexity and variability. However, without explicitly described processes there is no analysis and efficient communication of best practices of individual knowledge work within the organization. In addition, the activities of the individual knowledge work cannot be synchronized with the activities in the organizational knowledge work.rnrnSolution to this problem is the semantic integration of individual knowledgernwork and organizational knowledge work by means of the patternbased core ontology strukt. The ontology allows for defining and managing the dynamic tasks of individual knowledge work in a formal way and to synchronize them with organizational business processes. Using the strukt ontology, we have implemented a prototype application for knowledge workers and have evaluated it at the use case of an architectural fifirm conducting construction projects.
With the Multimedia Metadata Ontology (M3O), we have developed a sophisticated model for representing among others the annotation, decomposition, and provenance of multimedia metadata. The goal of the M3O is to integrate the existing metadata standards and metadata formats rather than replacing them. To this end, the M3O provides a scaffold needed to represent multimedia metadata. Being an abstract model for multimedia metadata, it is not straightforward how to use and specialize the M3O for concrete application requirements and existing metadata formats and metadata standards. In this paper, we present a step-by-step alignment method describing how to integrate and leverage existing multimedia metadata standards and metadata formats in the M3O in order to use them in a concrete application. We demonstrate our approach by integrating three existing metadata models: the Core Ontology on Multimedia (COMM), which is a formalization of the multimedia metadata standard MPEG-7, the Ontology for Media Resource of the W3C, and the widely known industry standard EXIF for image metadata
In dieser Ausarbeitung beschreibe ich die Ergebnisse meiner Untersuchungen zur Erweiterung des LogAnswer-Systemsmit nutzerspezifischen Profilinformationen. LogAnswer ist ein natürlichsprachliches open-domain Frage-Antwort-System. Das heißt: es beantwortet Fragen zu beliebigen Themen und liefert dabei konkrete (möglichst knappe und korrekte) Antworten zurück. Das System wird im Rahmen eines Gemeinschaftsprojekts der Arbeitsgruppe für künstliche Intelligenz von Professor Ulrich Furbach an der Universität Koblenz-Landau und der Arbeitsgruppe Intelligent Information and Communication Systems (IICS) von Professor Hermann Helbig an der Fernuniversität Hagen entwickelt. Die Motivation meiner Arbeit war die Idee, dass der Prozess der Antwortfindung optimiert werden kann, wenn das Themengebiet, auf das die Frage abzielt, im Vorhinein bestimmt werden kann. Dazu versuchte ich im Rahmen meiner Arbeit die Interessensgebiete von Nutzern basierend auf Profilinformationen zu bestimmen. Das Semantic Desktop System NEPOMUK wurde verwendet um diese Profilinformationen zu erhalten. NEPOMUK wird verwendet um alle Daten, Dokumente und Informationen, die ein Nutzer auf seinem Rechner hat zu strukturieren. Dazu nutzt das System ein sogenanntes Personal Information Model (PIMO) in Form einer Ontologie. Diese Ontologie enthält unter anderem eine Klasse "Topic", welche die wichtigste Grundlage für das Erstellen der in meiner Arbeit verwendeten Nutzerprofile bildete. Konkret wurde die RDF-Anfragesprache SPARQL verwendet, um eine Liste aller für den Nutzer relevanten Themen aus der Ontologie zu filtern. Die zentrale Idee meiner Arbeit war es nun diese Profilinformationen zur Optimierung des Ranking von Antwortkandidaten einzusetzen. In LogAnswer werden zu jeder gestellten Frage bis zu 200 potentiell relevante Textstellen aus der deutschen Wikipedia extrahiert. Diese Textstellen werden auf Basis von Eigenschaften (wie z.B. lexikalische Übereinstimmungen zwischen Frage und Textstelle) geordnet, da innerhalb des zur Verfügung stehenden Zeitlimits nicht alle Kandidaten bearbeitet werden können.
Mein Ansatz verfolgte das Ziel, diesen Algorithmus durch Nutzerprofile so zu erweitern, dass Antwortkandidaten, welche für den Benutzer relevante Informationen enthalten, höher in der Rangfolge eingeordnet werden. Zur Umsetzung dieser Idee musste eine Methode gefunden werden, um zu bestimmen ob ein Antwortkandidat mit dem Profil übereinstimmt. Da sich die in einer Textstelle enthaltenen Informationen in den meisten Fällen auf das übergeordnete Thema des Artikels beziehen, ohne den Namen des Artikels explizit zu erwähnen, wurde in meiner Implementierung der Artikelname betrachtet, um zu ermitteln, zu welchem Themengebiet die Textstelle Informationen liefert. Als zusätzliches Hilfsmittel wurde außerdem die DBpedia-Ontologie eingesetzt, welche die Informationen der Wikipedia strukturiert im RDF Format enthält. Mit Hilfe dieser Ontologie war es möglich, jeden Artikel in Kategorien einzuordnen, die dann mit den im Profil enthaltenen Stichworten verglichen wurden. Zur Untersuchung der Auswirkungen des Ansatzes auf das Ranking-Verfahren wurden mehrere Testläufe mit je 200 Testfragen durchgeführt. Die erste Testmenge bestand aus zufällig ausgewählten Fragen, die mit meinem eigenen Nutzerprofil getestet wurden. Dieser Testlauf lieferte kaum nutzbare Ergebnisse, da nur bei 29 der getesteten Fragen überhaupt ein Antwortkandidat mit dem Profil in Verbindung gebracht werden konnte. Außerdem konnte eine potentielle Verbesserung der Ergebnisse nur bei einer dieser 29 Fragen festgestellt werden, was zu der Schlussfolgerung führte, dass der Einsatz von Profildaten nicht für Anwendungsfälle geeignet ist, in denen die Fragen keine Korrelation mit dem genutzten Profil aufweisen.
Da die Grundannahme meiner Arbeit war, dass Nutzer in erster Linie Fragen zu den Interessensgebieten stellen, welche sich aus ihrem Profil ableiten lassen, sollten die weiteren Testläufe genau diesen Fall beleuchten. Dazu wurden 200 Testfragen aus dem Bereich Sport ausgewählt und mit einem Profil getestet, welches Stichworte zu unterschiedlichen Sportarten enthielt. Die Tests mit den Sportfragen waren wesentlich aussagekräftiger. Auch hier deuteten die Ergebnisse darauf hin, dass der Ansatz kein großes Potential zur Verbesserung des Rankings hat. Eine genauere Betrachtung einiger ausgewählter Beispiele zeigte allerdings, dass die Integration von Profildaten für bestimmte Anwendungsfälle, wie z.B. offene Fragen für die es mehr als eine korrekte Antwort gibt, durchaus zu einer Verbesserung der Ergebnisse führen kann. Außerdem wurde festgestellt, dass viele der schlechten Ergebnisse auf Inkosistenzen in der DBpedia-Ontologie und grundsätzliche Probleme im Umgang mit Wissensbasen in natürlicher Sprache beruhen.
Die Schlussfolgerung meiner Arbeit ist, dass der in dieser Arbeit vorgestellte Ansatz zur Integration von Profilinformationen für den aktuellen Anwendungsfall von LogAnswer nicht geeignet ist, da vor allem Faktenwissen aus sehr unterschiedlichen Domänen abgefragt wird und offene Fragen nur einen geringen Anteil ausmachen.
Wild bees are essential for the pollination of wild and cultivated plants. However, within the
last decades, the increasing intensification of modern agriculture has led to both a reduction and fragmentation as well as a degradation of the habitats wild bees need. The resulting loss of pollinators and their pollination poses an immense challenge to global food production. To support wild bees, the availability of flowering resources is essential. However, the flowering period of each resource is temporally limited and has different effects on pollinators and their pollination, depending on the time of their flowering.
Therefore, to efficiently promote and manage wild bee pollinators in agricultural landscapes, we identified species-specific key floral resources of three selected wild bee species and their spatial and temporal availability (CHAPTERS 2, 3 & 4). We examined, which habitat types predominantly provide these resources (CHAPTERS 3 & 4). We also investigated whether floral resource maps based on the use of these key resources and their spatial and temporal availability explain the abundance and development of the selected wild bees (CHAPTERS 3 & 4) and pollination (CHAPTER 5) better than habitat maps, that only indirectly account for the availability of floral resources.
For each of the species studied, we were able to identify different key pollen sources, predominantly woody plants in the early season (April/May) and increasingly herbaceous plants in the later season (June/July; CHAPTERS 2, 3 & 4). The open woody semi-natural habitats of our agricultural landscapes provided about 75% of the floral resources for the buff-tailed bumblebees, 60% for the red mason bees, and 55% for the horned mason bees studied, although they accounted for only 3% of the area (CHAPTERS 3 & 4). In addition, fruit orchards provided about 35% of the floral resources for the horned mason bees on 4% of the landscape area (CHAPTER 3). We showed that both mason bee species benefited from the resource availability in the surrounding landscapes (CHAPTER 3). Yet this was not the case for the bumblebees (CHAPTER 4). Instead, the weight gain of their colonies, the number of developed queen cells and their colony survival were higher with increasing proximity to forests. The proximity to forests also had a positive effect on the mason bees studied (CHAPTER 3). In addition, the red mason bees benefited from herbaceous semi-natural habitats. The proportion of built-up areas had a negative effect on the horned mason bees, and the proportion of arable land on the red mason bees. The habitat maps explained horned mason bee abundances equally well as the floral resource maps, but red mason bee abundances were distinctly better explained by key floral resources. The pollination of field bean increased with higher proportions of early floral resources, whereas synchronous floral resources showed no measurable reduction in their pollination (CHAPTER 5). Habitat maps also explained field bean pollination better than floral resource maps. Here, pollination increased with increasing proportions of built-up areas in the landscapes and decreased with increasing proportions of arable land.
Our results highlight the importance of the spatio-temporal availability of certain key species as resource plants of wild bees in agricultural landscapes. They show that habitat maps are ahead of, or at least equal to, spatio-temporally resolved floral resource maps in predicting wild bee development and pollination. Nevertheless, floral resource maps allow us to draw more accurate conclusions between key floral resources and the organisms studied. The proximity to forest edges had a positive effect on each of the three wild bee species studied. However, besides pure food availability, other factors seem to co-determine the occurrence of wild bees in agricultural landscapes.
The term "Augmented Reality (AR)" denotes the superposition of additional virtual objects and supplementary information over real images. The joint project Enhanced Reality (ER)1 aims at a generic AR-system. The ER-project is a cooperation of six different research groups of the Department of Computer Science at the University of Koblenz-Landau. According to Ronald Azuma an AR-system combines real and virtual environments, where the real and virtual objects are registered in 3-D, and it provides interactivity in real time [Azu97]. Enhanced Reality extends Augmented Reality by requiring the virtual objects to be seamlessly embedded into the real world as photo-realistic objects according to the exact lighting conditions. Furthermore, additional information supplying value-added services may be displayed and interaction of the user may even be immersive. The short-term goal of the ER-project is the exploration of ER-fundamentals using some specific research scenarios; the long-term goal is the development of a component-based ER-framework for the creation of ER-applications for arbitrary application areas. ER-applications are developed as single-user applications for users who are moving in a real environment and are wearing some kind of visual output device like see-through glasses and some mobile end device. By these devices the user is able to see reality as it is, but he can also see the virtual objects and the additional information about some value-added service. Furthermore he might have additional devices whereby he can interact with the available virtual objects. The development of a generic framework for ER-applications requires the definition of generic components which are customizable and composable to build concrete applications and it requires a homogeneous data model which supports all components equally well. The workgroup "Software Technology"2 is responsible for this subproject. This report gives some preliminary results concerning the derivation of a component-based view of ER. There are several augmented reality frameworks like ARVIKA, AMIRE, DWARF, MORGAN, Studierstube and others which offer some support for the development of AR-applications. All of them ease the use of existing subsystems like AR-Toolkit, OpenGL and others and leverage the generation process for realistic systems by making efficient use of those subsystems. Consequently, they highly rely on them.
Sediment transport contributes to the movement of inorganic and organic material in rivers. The construction of a dam interrupts the continuity of this sediment transport through rivers, causing sediments to accumulate within the reservoir. Reservoirs can also act as carbon sinks and methane can be released when organic matter in the sediment is degraded under anoxic conditions. Reservoir sedimentation poses a great threat to the sustainability of reservoirs worldwide, and can emit the potent greenhouse gas methane into the atmosphere. Sediment management measures to rehabilitate silted reservoirs are required to achieve both better water quantity and quality, as well as to mitigate greenhouse gas emissions.
This thesis aims at the improvement of sediment sampling techniques to characterize sediment deposits as a basis for accurate and efficient water jet dredging and to monitor the dredging efficiency by measuring the sediment concentration. To achieve this, we investigated freeze coring as a method to sample (gas-bearing) sediment in situ. The freeze cores from three reservoirs obtained were scanned using a non-destructive X-Ray CT scan technique. This allows the determination of sediment stratification and character-ization of gas bubbles to quantify methane emissions and serve as a basis for the identi-fication of specific (i.e. contaminated) sediment layers to be dredged. The results demon-strate the capability of freeze coring as a method for the characterization of (gas-bearing) sediment and overcomes certain limitations of commonly used gravity cores. Even though the core’s structure showed coring disturbances related to the freezing process, the general core integrity seems to not have been disturbed. For dredging purposes, we analyzed the impact pressure distribution and spray pattern of submerged cavitating wa-ter jets and determined the effects of impinging distances and angles, pump pressures and spray angles. We used an adapted Pressure Measurement Sensing technique to enhance the spatial distribution, which proved to be a comparatively easy-to-use meas-urement method for an improved understanding of the governing factors on the erosional capacity of cavitating water jets. Based on this data, the multiple linear regression model can be used to predict the impact pressure distribution of those water jets to achieve higher dredging accuracy and efficiency. To determine the dredging operational efficien-cy, we developed a semi-continuous automated measurement device to measure the sediment concentration of the slurry. This simple and robust device has lower costs, compared to traditional and surrogate sediment concentration measurement technolo-gies, and can be monitored and controlled remotely under a wide range of concentrations and grain-sizes, unaffected by entrained gas bubbles
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.
Navigation is a natural way to explore and discover content in a digital environment. Hence, providers of online information systems such as Wikipedia---a free online encyclopedia---are interested in providing navigational support to their users. To this end, an essential task approached in this thesis is the analysis and modeling of navigational user behavior in information networks with the goal of paving the way for the improvement and maintenance of web-based systems. Using large-scale log data from Wikipedia, this thesis first studies information access by contrasting search and navigation as the two main information access paradigms on the Web. Second, this thesis validates and builds upon existing navigational hypotheses to introduce an adaptation of the well-known PageRank algorithm. This adaptation is an improvement of the standard PageRank random surfer navigation model that results in a more "reasonable surfer" by accounting for the visual position of links, the information network regions they lead to, and the textual similarity between the link source and target articles. Finally, using agent-based simulations, this thesis compares user models that have a different knowledge of the network topology in order to investigate the amount and type of network topological information needed for efficient navigation. An evaluation of agents' success on four different networks reveals that in order to navigate efficiently, users require only a small amount of high-quality knowledge of the network topology. Aside from the direct benefits to content ranking provided by the "reasonable surfer" version of PageRank, the empirical insights presented in this thesis may also have an impact on system design decisions and Wikipedia editor guidelines, i.e., for link placement and webpage layout.
Abstract The present work investigates the wetting characteristics of soils with regard to their dependence on environmental parameters such as water content (WC), pH, drying temperature and wetting temperature of wettable and repellent soils from two contrasting anthropogenic sites, the former sewage disposal field Berlin-Buch and the inner-city park Berlin-Tiergarten. The aim of this thesis is to deepen the understanding of processes and mechanisms leading to changes in soil water repellency. This helps to gain further insight into the behaviour of soil organic matter (SOM) and identifying ways to prevent or reduce the negative effects of soil water repellency (SWR). The first focus of this work is to determine whether chemical reactions are required for wetting repellent samples. This hypothesis was tested by time and temperature dependence of sessile drop spreading on wettable and repellent samples. Additionally, diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy was used to determine whether various drying regimes cause changes in the relative abundance of hydrophobic and hydrophilic functional groups in the outer layer of soil particles and whether these changes can be correlated with water content and the degree of SWR. Finally, by artificially altering the pH in dried samples applying acidic and alkaline reagents in a gaseous state, the influence of only pH on the degree of SWR was investigated separately from the influence of changes in moisture status. The investigation of the two locations Buch and Tiergarten, each exceptionally different in the nature of their respective wetting properties, leads to new insights in the variety of appearance of SWR. The results of temperature, water content and pH dependency of SWR on the two contrasting sites resulted in one respective hypothetical model of nature of repellency for each site which provides an explanation for most of the observations made in this and earlier studies: At the Tiergarten site, wetting characteristics are most likely determined by micelle-like arrangement of amphiphiles which depends on the concentration of water soluble amphiphilic substances, pH and ionic strength in soil solution. At low pH and at high ionic strength, repulsion forces between hydrophilic charged groups are minimized allowing their aggregation with outward orientated hydrophobic molecule moieties. At high pH and low ionic strength, higher repulsion forces between hydrophilic functional groups lead to an aggregation of hydrophobic groups during drying, which results in a layer with outward oriented hydrophilic moieties on soil organic matter surface leading to enhanced wettability. For samples from the Buch site, chemical reactions are necessary for the wetting process. The strong dependence of SWR on water content indicates that hydrolysis-condensation reactions are the controlling mechanisms. Since acid catalyzed hydrolysis is an equilibrium reaction dependent on water content, an excess of water favours hydrolysis leading to an increasing number of hydrophilic functional groups. In contrast, water deficiency favours condensation reactions leading to a reduction of hydrophilic functional groups and thus a reduction of wettability. The results of the present investigation and its comparison with earlier investigations clearly show that SWR is subject to numerous antagonistically and synergistically interacting environmental factors. The degree of influence, which a single factor exerts on SWR, is site-specific, e.g., it is dependent on special characteristics of mineral constituents and SOM which underlies the influence of climate, soil texture, topography, vegetation and the former and current use of the respective site.
Technical products have become more than practical tools to us. Mobile phones, for example, are a constant companion in daily life. Besides purely pragmatic tasks, they fulfill psychological needs such as relatedness, stimulation, competence, popularity, or security. Their potential for the mediation of positive experience makes interactive products a rich source of pleasure. Research acknowledged this: in parallel to the hedonic/utilitarian model in consumer research, Human-Computer Interaction (HCI) researchers broadened their focus from mere task-fulfillment (i.e., the pragmatic) to a holistic view, encompassing a product's ability for need-fulfillment and positive experience (i.e., the hedonic). Accordingly, many theoretical models of User Experience (UX) acknowledge both dimensions as equally important determinants of a product's appeal: pragmatic attributes (e.g., usability) as well as hedonic attributes (e.g., beauty). In choice situations, however, people often overemphasize the pragmatic, and fail to acknowledge the hedonic. This phenomenon may be explained by justification. Due to their need for justification, people attend to the justifiability of hedonic and pragmatic attributes rather than to their impact on experience. Given that pragmatic attributes directly contribute to task-fulfillment, they are far easier to justify than hedonic attributes. People may then choose the pragmatic over the hedonic, despite a true preference for the hedonic. This can be considered a dilemma, since people choose what is easy to justify and not what they enjoy the most. The present thesis presents a systematic exploration of the notion of a hedonic dilemma in the context of interactive products.
A first set of four studies explored the assumed phenomenon. Study 1 (N = 422) revealed a reluctance to pay for a hedonic attribute compared to a pragmatic attribute. Study 2 (N = 134) demonstrated that people (secretly) prefer a more hedonic product, but justify their choice by spurious pragmatic advantages. Study 3 (N = 118) confronted participants with a trade-off between hedonic and pragmatic quality. Even though the prospect of receiving a hedonic product was related to more positive affect, participants predominantly chose the pragmatic, especially those with a high need for justification. This correlation between product choice and perceived need for justification lent further support to the notion that justification lies at the heart of the dilemma. Study 4 (N = 125) explored affective consequences and justifications provided for hedonic and pragmatic choice. Data on positive affect suggested a true preference for the hedonic - even among those who chose the pragmatic product.
A second set of three studies tested different ways to reduce the dilemma by manipulating justification. Manipulations referred to the justifiability of attributes as well as the general need for justification. Study 5 (N = 129) enhanced the respective justifiability of hedonic and pragmatic choice by ambiguous product information, which could be interpreted according to latent preferences. As expected, enhanced justifiability led to an increase in hedonic but not in pragmatic choice. Study 6 (N = 178) manipulated the justifiability of hedonic choice through product information provided by a "test report", which suggested hedonic attributes as legitimate. Again, hedonic choice increased with increased justifiability. Study 7 (N = 133) reduced the general need for justification by framing a purchase as gratification. A significant positive effect of the gratification frame on purchase rates occurred for a hedonic but not for a pragmatic product.
Altogether, the present studies revealed a desire for hedonic attributes, even in interactive products, which often are still understood as purely pragmatic "tools". But precisely because of this predominance of pragmatic quality, people may hesitate to give in to their desire for hedonic quality in interactive products - at least, as long as they feel a need for justification. The present findings provide an enhanced understanding of the complex consequences of hedonic and pragmatic attributes, and indicate a general necessity to expand the scope of User Experience research to the moment of product choice. Limitations of the present studies, implications for future research as well as practical implications for design and marketing are discussed.
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.