Distributed sensor networks are highly prone to accidental errors and malicious activities, owing to their limited resources and tight interaction with the environment. Yet only a...
Claudio Basile, Meeta Gupta, Zbigniew Kalbarczyk, ...
In parallel computing environments such as HPC clusters and the Grid, data-intensive applications involve large overhead costs due to a concentration of access to the files on co...
Results of an experimental study of an anomaly detection system based on the paradigm of artificial immune systems (AISs) are presented. Network traffic data are mapped into ant...
Recent advances in LiDAR (Light Detection and Ranging) technology have allowed for the remote sensing of important forest characteristics to be more reliable and commercially avail...
We propose a discriminative learning approach for fusing multichannel sequential data with application to detect unsafe driving patterns from multi-channel driving recording data....