Background: In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interact...
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
We present a text-based approach for the automatic indexing and retrieval of digital photographs taken at crime scenes. Our research prototype, SOCIS, goes beyond keyword-based ap...
— Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently...
Matthew Howard, Stefan Klanke, Michael Gienger, Ch...
A core problem in Model Driven Engineering is model consistency achievement: all models must satisfy relationships constraining them. Active consistency techniques monitor and cont...
Gregory de Fombelle, Xavier Blanc, Laurent Rioux, ...