Computer Science

Internet access networks in general and wireless mesh access networks in particular, are the bottleneck of today’s communication networks and consequently most strongly responsible for determining the user satisfaction. The limited bandwidth and the fact that access network are most often used as mere bit pipes are however unfavorable for the users’ quality of experience (QoE). The lack of application-specific service guarantees is especially inadequate in the face of an increasing degree of heterogeneity of Internet applications and their individual service requirements. Application and quality of experience resource management, Aquarema for short, addresses this challenge by enabling application specific network resource management and thereby improves the user QoE. This is achieved by the interaction of application comfort (AC) monitoring tools, running at the clients, and a network advisor which may trigger different resource management tools. AC quantifies how well an application is running and in particular, enables a prediction of the user experience, thereby allowing the network advisor to act upon an imminent QoE degradation. We demonstrate the appeal of Aquarema at the example of YouTube video streaming in a congested IEEE 802.11 based mesh testbed where AC-aware traffic shaping guarantees the successful video playback.

This article studies an implementation methodology for partial and disjunctive stable models where partiality and disjunctions are unfolded from a logic program so that an implementation of stable models for normal (disjunction-free) programs can be used as the core inference engine. The unfolding is done in two separate steps. First, it is shown that partial stable models can be captured by total stable models using a simple linear and modular program transformation. Hence, reasoning tasks concerning partial stable models can be solved using an implementation of total stable models. Disjunctive partial stable models have been lacking implementations which now become available as the translation handles also the disjunctive case. Second, it is shown how total stable models of disjunctive programs can be determined by computing stable models for normal programs. Thus an implementation of stable models of normal programs can be used as a core engine for implementing disjunctive progra...

In the last years, ontologies have played a major role for building large, distributed, and heterogeneous intelligent systems. E.g., ontologies are one key technique of the semantic web layer. The development process of an ontology heavily depends on its evaluation. In this paper, we introduce several measures for the evaluation of ontological knowledge. Besides standard methods like taxonomic errors we also present novel metrics focusing on design anomalies. For the implementation of these measures we propose a declarative approach using the logic-based language FNQuery.

The ontology web language Owl has been established as a standardized representation for knowledge, especially in the context of the semantic web. An important facet of the management of such knowledge bases consists in its evaluation. Besides standard evaluation methods described in the literature particular applications can require to consider further measures. In this paper, we use a declarative, logicbased Xml query and transformation language called FnQuery, which is suitable for exibly dening queries for evaluating Owlbased knowledge. The queries are evaluated using logic programming and nonmonotonic reasoning systems. The presented approach could be extended to handle complex refactorings as well.

We consider multilevel set-covering models for diagnostic reasoning: though a lot of work has been done in this field, knowledge acquisition efforts have been investigated only insufficiently. We will show how set-covering models can be build incrementally and how they can be refined by knowledge enhancements or representational extensions. All these extensions have a primary characteristic: they can be applied without changing the basic semantics of the model.

We introduce an agile process model for the development of diagnostic knowledge systems. As key practices of this evolutionary process model we identify structured modifications of the knowledge by restructuring methods, and the continuous validation of the knowledge using automated testing methods. Finally, we report promising experiences gained by the evaluation of a development project implementing a medical documentation and consultation system.

The development of knowledge systems has been investigated since the seventies and many process models have been proposed to reduce knowledge acquisition costs and to increase system quality. Recently, agile process models, e.g., eXtreme programming, have discussed extensively in the software engineering community. They appeared to be appropriate for small-sized teams and proved to be very successful in various projects. In this paper, we introduce an agile process model for developing diagnostic knowledge systems, which can provide an alternative to well-accepted methodologies like CommonKADS, e.g., if the team size is small or specifications are vague.

For the development of practical semantic applications, ontologies are commonly used with rule extensions. Prominent examples of semantic applications are Semantic Wikis, Semantic Desktops, but also advanced Web Services and agents. The application of rules increases the expressiveness of the underlying knowledge in many ways. Likewise, the integration creates new challenges for the design process of such ontologies, but also existing evaluation methods have to cope with the extension of ontologies by rules. Since the verification of OWL ontologies with rule extensions is not tractable in general, we propose to verify ontologies at the symbolic level by using a declarative approach: With the new language DATALOG , known anomalies can be easily specified and tested in a compact manner. We introduce supplements to existing verification techniques to support the design of ontologies with rule enhancements, and we focus on the detection of anomalies that especially occur due to the combined use of rules and ontological definitions.

The increasing complexity of protein interaction networks makes their manual analysis infeasible. Signal transduction processes pose a specific chal- lenge, as each protein can perform different functions, depending on its state. Here, we present a PROLOG and XML based system which explores the protein state space. Starting with state based information about the function of single proteins, the system searches for all biologically reasonable states that can be reached from the starting point. As facts of general molecular biology have been integrated, novel reasonable states, not encoded in the starting set, can be reached. Furthermore, the influence of modifications like mutations or the addition of fur- ther proteins can be explored. Thus, the system could direct experiments and allow to predict their outcome.

This paper investigates the novel concept of clausal deductive databases (cd-databases), which are special normal deductive databases – i.e., deductive databases which may contain default negation in rule bodies – over a typed meta-language Lcd with a fixed set of predicate symbols, namely dis, con, and some built-in predicate symbols. The arguments of the literals in Lcd are given by disjunctive and conjunctive clauses of a basic first-order language L. Disjunctive deductive databases (dd-databases) generalize normal deductive databases by allowing for disjunctions of atoms or literals in rule heads. We present a transformation which maps a dd-database D into a cd-database Dcd that talks about the clauses of D. cd-databases provide a flexible framework for declaratively specifying the semantics of dd-databases: we can fix a standard control strategy, e.g., stable model or well-founded semantics, and vary the logical descriptionDcd for specifying different semantics. The transformed...

Non {Horn programs containing disjunctive rules allow for more advanced applications of deductive databases. But the inference process dealing with rapidly increasing amounts of disjunctive facts becomes much more intricate, because of the ...

We investigate cardinality constraints of the form M,! K, where M is a set and is one of the comparison operators\=,", or\": a model of such a constraint is required to contain\ exactly, at most", or\ at least", respectively, K elements of M. Applications dealing with ...

A common problem in using and running RDBMS is performance, which highly depends on the quality of the database schema design and the resulting structure of the tables and the logical relations between them. In production reality, the performance ...

Practical applications of deductive databases often require the use of extended features like disjunctive information, aggregation operators or default negation. But it has been unclear how one could deal with aggregation in the presense of recursion and ...

Jedes q j (...) ist eine atomare Formel. Die q j werden oft als Subgoals bezeichnet. X 1 , ...,X m sind Variablen, die mindestens einmal auch auf der rechten Seite des Zeichens :-vorkommen müssen. p(...) ∨ ¬q 1 (...) ∨... ∨ ¬q n (...) Die Prädikate beginnen mit einem Kleinbuchstaben. Die zugehörigen Relationen-seien es EDB-oder IDB-Relationen-werden mit gleichem Namen, aber mit einem Großbuchstaben beginnend, bezeichnet.

Declarative Programming is an advanced paradigm for the modeling and solving of complex problems. This specification method has got more and more attraction over the last years, e.g., in the domains of databases and the processing of natural language, for the modeling and processing of combinatorial problems, and for establishing systems for the Web.

The maintenance of large knowledge systems usually is a rather complex task. In this paper we will show that extensions or modifications of a knowledge base can be supported by appropriate visualizations techniques, e.g. by illustrating dependencies of the considered knowledge. In particular, we introduce a declarative approach for querying and visualizing rule-based knowledge represented as XML documents; a knowledge engineer can extract and visually inspect parts of the knowledge base by ad-hoc declarations in a flexible manner.