In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
Most work to date in parallel and distributed discrete event simulation is based on assigning precise time stamps to events, and time stamp order event processing. An alternative ...
We consider query optimization techniques for data intensive P2P applications. We show how to adapt an old technique from deductive databases, namely Query-Sub-Query (QSQ), to a s...
The number of processors embedded on high performance computing platforms is continuously increasing to accommodate user desire to solve larger and more complex problems. However,...
Thara Angskun, George Bosilca, Graham E. Fagg, Jel...