Time-varying spatial patterns are common, but few computational tools exist for discovering and tracking multiple, sometimes overlapping, spatial structures of targets. We propose...
—Developing powerful paradigms for programming sensor networks is critical to realize the full potential of sensor networks as collaborative data processing engines. In this arti...
: The next generation of scientific experiments and studies, popularly called as e-Science, is carried out by large collaborations of researchers distributed around the world engag...
Srikumar Venugopal, Rajkumar Buyya, Lyle J. Winton
A key advantage of scientific workflow systems over traditional scripting approaches is their ability to automatically record data and process dependencies introduced during workf...
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...