Stochastic context-free grammars (SCFG) have been used in RNA Secondary structure modeling. An SCFG consists of a set of grammar rules with probability for each. Given a grammar design, finding the best set of probabilities that yield optimum performance can be challenging. Although current Expectation Maximization (EM) MaximumLikelihood (ML)-based model training approaches have been effective,...

The discovery of small molecules targeted to specific oncogenic pathways has revolutionized anti-cancer therapy. However, such therapy often fails due to the evolution of acquired resistance. One long-standing question in clinical cancer research is the identification of optimum therapeutic administration strategies so that the risk of resistance is minimized. In this paper, we investigate opti...

Antenna designers are constantly challenged with the temptation to search for optimum solutions for the design of complex electromagnetic devices. The ability of using numerical methods to accurately and efficiently characterizing the relative quality of a particular design has excited the engineers to apply stochastic global evolutionary optimizers (EO) for this objective. EO techniques have b...

Motivated by the Internet-of-things and sensor networks for cyberphysical systems, the problem of dynamic sensor activation for the tracking of a time-varying process is examined. The tradeoff is between energy efficiency, which decreases with the number of active sensors, and fidelity, which increases with the number of active sensors. The problem of minimizing the time-averaged mean-squared e...