In this paper we present an improved scheduling technique for the synthesis of time-triggered embedded systems. Our system model captures both the flow of data and that of control...
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
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 ...
Abstract. As wireless sensor networks gain in popularity, many deployments are posing new challenges due to their diverse topologies and resource constraints. Previous work has sho...
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...