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The performance of napkins is nowadays improved substantially by embedding granules of a superabsorbent into the cellulose matrix. In this paper a continuous model for the liquid transport in such an Ultra Napkin is proposed. Its mean feature is a nonlinear diffusion equation strongly coupled with an ODE describing a reversible absorbtion process. An efficient numerical method based on a symmetrical time splitting and a finite difference scheme of ADI-predictor-corrector type has been developed to solve these equations in a three dimensional setting. Numerical results are presented that can be used to optimize the granule distribution.

For the online collision detection with a multi-arm robot a fast method for computing the so-called collision vector is presented. Manipulators and obstacles are modelled by sets of convex polytopes. Known distance algorithms serve as a foundation. To speed up the collision detection dynamic obstacles are approximated by geometric primitives and organized in hierarchies. On-line, the here introduced Dynamic Hierarchies are adjusted to the current arm configuration. A comparison with previous methods shows an increased acceleration of the computations.

In this paper we present an interpreter which allows to support the validation of conceptual models in early stages of the development. We compare hypermedia and expert system approaches to knowledge processing and show how an integrated approach eases the creation of expert systems. Our knowledge engineering tool CoMo-Kit allows a "smooth" transition from initial protocols via a semi-formal specification based on a typed hypertext up to an running expert system. The interpreter uses the intermediate hypertext representation for the interactive solution of problems. Thereby, tasks are distributed to agents via an local area network. This means that the specification of an expert system can directly be used to solve real world problems. If there exist formal (operational) specifications for subtasks then these are delegated to computers. Therefore, our approach allows to specify and validate distributed, cooperative systems where some subtasks are solved by humans and other subtasks are solved automatically by computers.

Four different initialization methods for parallel Branch-and-bound algorithms are described and compared with reference to several criteria. A formal analysis of their idle times and efficiency follows. It indicates that the efficiency of three methods depends on the branching factor of the search tree. Furthermore, the fourth method offers the best efficiency of the overall algorithm when a centralized OPEN set is used. Experimental results by a PRAM simulation support these statements.

The introduction of sorts to first-order automated deduc-tion has brought greater conciseness of representation and a considerablegain in efficiency by reducing search spaces. This suggests that sort in-formation can be employed in higher-order theorem proving with similarresults. This paper develops a sorted (lambda)-calculus suitable for automatictheorem proving applications. It extends the simply typed (lambda)-calculus by ahigher-order sort concept that includes term declarations and functionalbase sorts. The term declaration mechanism studied here is powerfulenough to subsume subsorting as a derived notion and therefore gives ajustification for the special form of subsort inference. We present a set oftransformations for sorted (pre-) unification and prove the nondetermin-istic completeness of the algorithm induced by these transformations.

In this paper we describe a framework for defining and operationalizing conceptual models of distributed knowledge-based systems which extends published approaches by the notion of ,agents" and multiple task decompositions. The main part deals with techniques underlying our distributed interpreter. We show how a client-server-architecture can be implemented which allows prototyping distributed knowledge-based systems. Further we describe our mechanism which manages task interactions and supports dependency-directed backtracking efficiently.

A method for efficiently handling associativity and commutativity (AC) in implementations of (equational) theorem provers without incorporating AC as an underlying theory will be presented. The key of substantial efficiency gains resides in a more suitable representation of permutation-equations (such as f(x,f(y,z))=f(y,f(z,x)) for instance). By representing these permutation-equations through permutations in the mathematical sense (i.e. bijective func- tions :{1,..,n} {1,..,n}), and by applying adapted and specialized inference rules, we can cope more appropriately with the fact that permutation-equations are playing a particular role. Moreover, a number of restrictions concerning application and generation of permuta- tion-equations can be found that would not be possible in this extent when treating permu- tation-equations just like any other equation. Thus, further improvements in efficiency can be achieved.

This paper presents fill algorithms for boundary-defined regions in raster graphics. The algorithms require only a constant size working memory. The methods presented are based on the so-called "seed fill" algorithms using the internal connectivity of the region with a given inner point. Basic methods as well as additional heuristics for speeding up the algorithm are described and verified. For different classes of regions, the time complexity of the algorithms is compared using empirical results.