Knowledge compilation is a common technique for propositional logic knowledge bases. The idea is to transform a given knowledge base into a special normal form ([MR03],[DH05]), for which queries can be answered efficiently. This precompilation step is very expensive but it only has to be performed once. We propose to apply this technique to knowledge bases defined in Description Logics. For this, we introduce a normal form, called linkless concept descriptions, for ALC concepts. Further we present an algorithm, based on path dissolution, which can be used to transform a given concept description into an equivalent linkless concept description. Finally we discuss a linear satisfiability test as well as a subsumption test for linkless concept descriptions.

The goal of this thesis is to develop a video retrieval system that supports relevance feedback. One research approach of the thesis is to find out if a combination of implicit and explicit relevance feedback returns better retrieval results than a system using explicit feedback only. Another approach is to identify a model to weight existing feature categories. For this purpose, a state-of-the-art analysis is presented and two systems implemented, which run under the conditions of the international TRECVID workshop. It will be a basis system for further research approaches in the field of interactive video retrieval. Amongst others, it shall participate in the 2006 search task of the mentioned workshop.

Dieses Dokument beschäftigt sich mit der Anbindung des w3100a-TCP/IP-Chips an einen AVR ATmega162 Mikrocontroller. Die Ansteuerung des Netzwerkchips erfolgt, um eine gute Adaptierbarkeit zu gewährleisten, durch eine C-Bibliothek, die in ihrer Funktionsweise der C-Socketbibliothek ähnelt.

The high cost of routing infrastructure makes checking theories about larger nets a very difficult and expensive task. One possible approach to fight this problem is the use of virtual instead of physical infrastructure. OPNet- IT Guru software is a suite designed to simulate large nets and present relevant information. This allows validating extensive changes before actually implementing them on a productive network or testing theories without the overhead of a physical infrastructure.

The Living Book is a system for the management of personalized and scenario specific teaching material. The main goal of the system is to support the active, explorative and self­determined learning in lectures, tutorials and self study. The Living Book includes a course on 'logic for computer scientists' with a uniform access to various tools like theorem provers and an interactive tableau editor. It is routinely used within teaching undergraduate courses at our university. This paper describes the Living Book and the use of theorem proving technology as a core component in the knowledge management system (KMS) of the Living Book. The KMS provides a scenario management component where teachers may describe those parts of given documents that are relevant in order to achieve a certain learning goal. The task of the KMS is to assemble new documents from a database of elementary units called 'slices' (definitions, theorems, and so on) in a scenario-based way (like 'I want to prepare for an exam and need to learn about resolution'). The computation of such assemblies is carried out by a model-­generating theorem prover for first-­order logic with a default negation principle. Its input consists of meta data that describe the dependencies between different slices, and logic-­programming style rules that describe the scenario-specific composition of slices. Additionally, a user model is taken into account that contains information about topics and slices that are known or unknown to a student. A model computed by the system for such input then directly specifies the document to be assembled. This paper introduces the e­learning context we are faced with, motivates our choice of logic and presents the newly developed calculus used in the KMS.