This paper addresses the problem of stochastic task execution time estimation agnostic to the process distributions. The proposed method is orthogonal to the application structure ...
Abstract. We present an improved adaptive approach for studying systems of ODEs affected by parameter variability and state space uncertainty. Our approach is based on a reformulat...
Background: Modelling the ligand binding site of a protein is an important component of understanding proteinligand interactions and is being actively studied. Even if the side ch...
Dynamic and partial reconfiguration discovers more and more the focus in academic and industrial research. Modern systems in e.g. avionic and automotive applications exploit the p...
Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...