Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
— Even for a specific application, the design space of wireless sensor networks is enormous, and traditional disciplinary boundaries are disappearing in the search for efficien...
Considering the voltage drop constraint over a distributed model for power/ground (P/G) network, we study the following two problems for physical synthesis of sleep transistors: t...
The development of more and more complex distributed applications over large networks of computers has raised the problem of semantic interoperability across applications based on ...
Paolo Bouquet, Bernardo Magnini, Luciano Serafini,...
Abstract. In formal approaches, messages sent over a network are usually modeled by terms together with an equational theory, axiomatizing the properties of the cryptographic funct...