Model-based development of highly complex software systems leads to large models. Storing them in repositories offers the possibility to work with these models in a distributed env...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
This paper presents our approach to model distributed discrete event simulation systems in the framework of distributed graph transformation. We use distributed typed attributed g...
– Efficient implementations of the Discrete Fourier Transform (DFT) for GPUs provide good performance with large data sizes, but are not competitive with CPU code for small data ...
An unfavourable phenomenon is observed: current electronic markets are fragmented and have formed a set of autonomously distributed product information islands. This leads to hete...