The present study investigated the instructional value of signals for learning while comparing two animations that differed solely in the presence / absence of visual signals. Sig...
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
The Planets Testbed is an open access web application for the digital preservation community, providing an experimental framework for evaluating preservation tools and approaches i...
Brian Aitken, Seamus Ross, Andrew Lindley, Edith M...
This paper proposes a comprehensive modeling architecture for workloads on parallel computers using Markov chains in combination with state dependent empirical distribution functi...