Refine
Year of publication
- 2011 (39) (remove)
Document Type
- Part of Periodical (14)
- Doctoral Thesis (9)
- Diploma Thesis (5)
- Bachelor Thesis (4)
- Study Thesis (3)
- Conference Proceedings (2)
- Master's Thesis (2)
Language
- English (39) (remove)
Keywords
- computer clusters (3)
- Data Mining (2)
- Modellgetriebene Entwicklung (2)
- OWL <Informatik> (2)
- Ontologie <Wissensverarbeitung> (2)
- Software Engineering (2)
- artificial neural networks (2)
- classification (2)
- parallel algorithms (2)
- 8C model (1)
Institute
- Fachbereich 4 (23)
- Institut für Wirtschafts- und Verwaltungsinformatik (7)
- Institut für Informatik (6)
- Institute for Web Science and Technologies (4)
- Institut für Computervisualistik (3)
- Fachbereich 7 (2)
- Institut für Integrierte Naturwissenschaften, Abt. Biologie (2)
- Fachbereich 8 (1)
- Institut für Softwaretechnik (1)
We present a non-linear camera pose estimator, which is able to handle a combined input of point and line feature correspondences. For three or more correspondences, the estimator works on any arbitrary number and choice of the feature type, which provides an estimation of the pose on a preferably small and flexible amount of 2D-3D correspondences. We also give an analysis of different minimization techniques, parametrizations of the pose data, and of error measurements between 2D and 3D data. These will be tested for the usage of point features, lines and the combination case. The result shows the most stable and fast working non-linear parameter set for pose estimation in model-based tracking.
The paper is devoted to solving a problem of the development of the website of Russian municipal policlinics and provides a selection of a set of elements which should be posted on a website. Such elements are necessary to provide citizens with correct and ergonomic e-services. The insufficient development of an infrastructure of institutions of public and municipal administration (particularly, healthcare institutions) in Russia made it necessary to analyze webresources used in different countries at different levels of providing medical services. The information resources of medical treatment facilities of the United Kingdom, of the United Statesrnof America and of the Federal Republic of Germany were researched separately for three existing economic models of healthcare. A set of criteria for the assessment of medical webresources was developed.
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.
In this diploma thesis a skeleton-based matching technique for 2D shapes is introduced. First, current approaches for the matching of shapes will be presented. The basics of skeleton-based matchings will be introduced. In the context of this thesis, a skeleton-based matching approach was implemented as presented in the original paper. This implementation is evaluated by performing a similarity search in three shape databases. Strengths and limitations of the approach are pointed out. In addition, the introduced algorithm will be examined with respect to extending it towards matching of 3D objects. In particular, the approach is applied to medical data sets: Pre- and postoperative CT images of the abdominal aorta of one patient will be compared. Problems and approaches for matching of 3D objects in general and blood vessels in particular will be presented.
Folksonomies are Web 2.0 platforms where users share resources with each other. Furthermore, they can assign keywords (called tags) to the resources for categorizing and organizing the resources. Numerous types of resources like websites (Delicious), images (Flickr), and videos (YouTube) are supported by different folksonomies. The folksonomies are easy to use and thus attract the attention of millions of users. Together with the ease they offer, there are also some problems. This thesis addresses different problems of folksonomies and proposes solutions for these problems. The first problem occurs when users search for relevant resources in folksonomies. Often, the users are not able to find all relevant resources because they don't know which tags are relevant. The second problem is assigning tags to resources. Although many folksonomies (like Delicious) recommend tags for the resources, other folksonomies (like Flickr) do not recommend any tags. Tag recommendation helps the users to easily tag their resources. The third problem is that tags and resources are lacking semantics. This leads for example to ambiguous tags. The tags are lacking semantics because they are freely chosen keywords. The automatic identification of the semantics of tags and resources helps in reducing problems that arise from this freedom of the users in choosing the tags. This thesis proposes methods which exploit semantics to address the problems of search, tag recommendation, and the identification of tag semantics. The semantics are discovered from a variety of sources. In this thesis, we exploit web search engines, online social communities and the co-occurrences of tags as sources of semantics. Using different sources for discovering semantics reduces the efforts to build systems which solve the problems mentioned earlier. This thesis evaluates the proposed methods on a large scale data set. The evaluation results suggest that it is possible to exploit the semantics for improving search, recommendation of tags, and automatic identification of the semantics of tags and resources.
The aim of this dissertational work was to examine physiological (heart rate variability measures) and biomechanical parameters (step features) as possible anticipating indicators of psychological mood states. 420 participants (275 male and 145 female, age: M=34.7 years ± 9.7) engaged in a 60-minute slow endurance run while they were asked questions via a mobile answering and recording device. We measured several mood states, physiological measures, and biomechanical parameters. We used a latent growth curve analysis to examine the cross-lagged effects. Results demonstrated significant (p ≤.05) relationships between biomechanical shoe features anticipating psychological mood states, as well as psychological mood states anticipating physiological parameters.
MapReduce with Deltas
(2011)
The MapReduce programming model is extended slightly in order to use deltas. Because many MapReduce jobs are being re-executed over slightly changing input, processing only those changes promises significant improvements. Reduced execution time allows for more frequent execution of tasks, yielding more up-to-date results in practical applications. In the context of compound MapReduce jobs, benefits even add up over the individual jobs, as each job gains from processing less input data. The individual steps necessary in working with deltas are being analyzed and examined for efficiency. Several use cases have been implemented and tested on top of Hadoop. The correctness of the extended programming model relies on a simple correctness criterion.
This paper introduces Vocville, a causal online game for learning vocabularies. I am creating this application for my master thesis of my career as a "Computervisualist" (computer visions) for the University of Koblenz - Landau. The application is an online browser game based on the idea of the really successful Facebook game FarmVille. The application is seperated in two parts; a Grails application manages a database which holds the game objects like vocabulary, a Flex/Flash application generates the actual game by using these data. The user can create his own home with everything in it. For creating things, the user has to give the correct translation of the object he wants to create several times. After every query he has to wait a certain amount of time to be queried again. When the correct answer is given sufficient times, the object is builded. After building one object the user is allowed to build others. After building enough objects in one area (i.e. a room, a street etc.) the user can activate other areas by translating all the vocabularies of the previous area. Users can also interact with other users by adding them as neighbors and then visiting their homes or sending them gifts, for which they have to fill in the correct word in a given sentence.