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...
— Rain, snow, gaseous, cloud, fog, scintillation and other atmospheric properties can have a distorting effect on signal fidelity of Ku and Ka bands, thus resulting in excessive ...
Kamal Harb, Changcheng Huang, Anand Srinivasan, Br...
Rising interest in the applications of wireless sensor networks has spurred research in the development of computing systems for lowthroughput, energy-constrained applications. Un...
Abstract—Increasing interest in sensor networking and ubiquitous computing has created a trend towards embedding more and more intelligence into our surroundings. This enables th...
Sensor networks have been used in many surveillance systems, providing statistical information about monitored areas. Accurate counting information (e.g., the distribution
of the ...
Shuo Guo, Tian He, Mohamed F. Mokbel, John A. Stan...