Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
We present tools to support model-based security engineering on both the model and the code level. In the approach supported by these tools, one firstly specifies the securitycr...
Vicarious Learning is learning from watching others learn. We believe that this is a powerful model for computer-based learning. Learning episodes can be captured and replayed to ...
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
The rapid growth of service coordination languages creates a need for methodological support for coordination design. Coordination design differs from workflow design because a ...