004 Datenverarbeitung; Informatik
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The requirements of modern e-learning techniques change. Aspects such as community interaction, flexibility, pervasive learning and increasing mobility in communication habits become more important. To meet these challenges e-learning platforms must provide support on mobile learning. Most approaches try to adopt centralised and static e-learning mechanisms to mobile devices. However, often technically it is not possible for all kinds of devices to be connected to a central server. Therefore we introduce an application of a mobile e-learning network which operates totally decentralised with the help of an underlying ad hoc network architecture. Furthermore the concept of ad hoc messaging network (AMNET) is used as basis system architecture for our approach to implement a platform for pervasive mobile e-learning.
This contribution presents a quantitative evaluation procedure for Information Retrieval models and the results of this procedure applied on the enhanced Topic-based Vector Space Model (eTVSM). Since the eTVSM is an ontology-based model, its effectiveness heavily depends on the quality of the underlaying ontology. Therefore the model has been tested with different ontologies to evaluate the impact of those ontologies on the effectiveness of the eTVSM. On the highest level of abstraction, the following results have been observed during our evaluation: First, the theoretically deduced statement that the eTVSM has a similar effecitivity like the classic Vector Space Model if a trivial ontology (every term is a concept and it is independet of any other concepts) is used has been approved. Second, we were able to show that the effectiveness of the eTVSM raises if an ontology is used which is only able to resolve synonyms. We were able to derive such kind of ontology automatically from the WordNet ontology. Third, we observed that more powerful ontologies automatically derived from the WordNet, dramatically dropped the effectiveness of the eTVSM model even clearly below the effectiveness level of the Vector Space Model. Fourth, we were able to show that a manually created and optimized ontology is able to raise the effectiveness of the eTVSM to a level which is clearly above the best effectiveness levels we have found in the literature for the Latent Semantic Index model with compareable document sets.
1. Design and Composition of 3D Geoinformation Services Benjamin Hagedorn 2. Operating System Abstractions for Service-Based Systems Michael Schöbel 3. A Task-oriented Approach to User-centered Design of Service-Based Enterprise Applications Matthias Uflacker 4. A Framework for Adaptive Transport in Service- Oriented Systems based on Performance Prediction Flavius Copaciu 5. Asynchronicity and Loose Coupling in Service-Oriented Architectures Nikola Milanovic
The innovation of information techniques has changed many aspects of our life. In health care field, we can obtain, manage and communicate high-quality large volumetric image data by computer integrated devices, to support medical care. In this dissertation I propose several promising methods that could assist physicians in processing, observing and communicating the image data. They are included in my three research aspects: telemedicine integration, medical image visualization and image segmentation. And these methods are also demonstrated by the demo software that I developed. One of my research point focuses on medical information storage standard in telemedicine, for example DICOM, which is the predominant standard for the storage and communication of medical images. I propose a novel 3D image data storage method, which was lacking in current DICOM standard. I also created a mechanism to make use of the non-standard or private DICOM files. In this thesis I present several rendering techniques on medical image visualization to offer different display manners, both 2D and 3D, for example, cut through data volume in arbitrary degree, rendering the surface shell of the data, and rendering the semi-transparent volume of the data. A hybrid segmentation approach, designed for semi-automated segmentation of radiological image, such as CT, MRI, etc, is proposed in this thesis to get the organ or interested area from the image. This approach takes advantage of the region-based method and boundary-based methods. Three steps compose the hybrid approach: the first step gets coarse segmentation by fuzzy affinity and generates homogeneity operator; the second step divides the image by Voronoi Diagram and reclassifies the regions by the operator to refine segmentation from the previous step; the third step handles vague boundary by level set model. Topics for future research are mentioned in the end, including new supplement for DICOM standard for segmentation information storage, visualization of multimodal image information, and improvement of the segmentation approach to higher dimension.