Background: The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, thi...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
We examine distributed time-synchronization in mobile ad-hoc and sensor networks. The problem is to estimate the skews and offsets of clocks of all the nodes with respect to an arb...
The economic benefit of a certain development process or particular activity is usually unknown and indeed hard to predict. However, the cost-effectiveness of process improvement...
Analytical modeling is an alternative to detailed performance simulation with the potential to shorten the development cycle and provide additional insights. This paper proposes a...