Tangible user interfaces allowing multiple simultaneous contacts are by now well known as multi-touch devices. They add new dimensions to input possibilities compared with traditional single-pointer devices. At the same time, complexity of input interpretation increases, as well. Particularly recognition of predefined gestures requires sophisticated techniques to cope with multiple points of interaction. In this paper we present a novel approach for recognition of multi-touch gestures by means of a mathematical rule calculus. It allows abstract definition of multi-touch gestures. We further outline how to implement a framework to encapsulate the recognition algorithm, and demonstrate its success through a practical example obtained from an existing application.

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In this paper we propose a knowledge-based approach for the support of adaptive and context-aware behavior in autonomic systems. In order to provide meaningful and adequate behavior in the presence of dynamic (or adverse) environments systems must possess the ability to assess their current state on the basis of knowledge about themselves and their environments. We propose to use ontologies for the representation of knowledge and its integration into a general systems architecture supporting autonomic behavior. Especially we rely on fuzzy description logics in order to support robust automatic reasoning w.r.t. environmental conditions. We distinguish several aspects of knowledge and use multiset term rewriting to describe mechanisms of coordination between them. We discuss the advantages of our approach and give examples for paradigmatic applications.

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