J. E. Palo Tejada

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We introduce and study an artificial neural network inspired by the probabilistic receptor affinity distribution model of olfaction. Our system consists of N sensory neurons whose outputs converge on a single processing linear threshold element. The system's aim is to model discrimination of a single target odorant from a large number p of background(More)
In this paper we use a Terahertz (THz) time-domain system to image and analyze the structure of an artwork attributed to the Spanish artist Goya painted in 1771. The THz images show features that cannot be seen with optical inspection and complement data obtained with X-ray imaging that provide evidence of its authenticity, which is validated by other(More)
The United States Nuclear Regulatory Commission (USNRC) relies on Probabilistic Risk Assessment (PRA) as one of the main pillars of its risk-informed regulatory and oversight functions. In 2011, the South Texas Project Nuclear Operating Company (STPNOC) initiated a risk-informed project to resolve Generic Safety Issue 191 (GSI-191), which is related to the(More)
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