We study an online random linear network coding approach for time division duplexing (TDD) channels under Poisson arrivals. We model the system as a bulk-service queue with variabl...
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
We introduce XPORT, a profile-driven distributed data dissemination system that supports an extensible set of data types, profile types, and optimization metrics. XPORT efficientl...
The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using qu...