Regions which evolve over time are a significant aspect of many phenomena in geographic information science. Examples include areas in which a measured value (e.g. temperature, sal...
Matt Duckham, John G. Stell, Maria Vasardani, Mich...
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...
Dynamic geographic phenomena, such as forest fires and oil spills, can have dire environmental, sociopolitical, and economic consequences. Mitigating, if not preventing such events...
Christopher Farah, Cheng Zhong, Michael F. Worboys...
A distributed and locally reprogrammable address event receiver has been designed, in which incoming addressevents are monitored simultaneously by all synapses, allowing for arbitr...
Simeon A. Bamford, Alan F. Murray, David J. Willsh...
: A Bayesian distributed online change detection algorithm is proposed for monitoring a dynamical system by a wireless sensor network. The proposed solution relies on modelling the...