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Electrical and Computer Engineering Commons™
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Articles 1 - 4 of 4
Full-Text Articles in Electrical and Computer Engineering
Trends In Uspto Office Actions, Ron D. Katznelson
Trends In Uspto Office Actions, Ron D. Katznelson
Ron D. Katznelson
No abstract provided.
Electric Power: Cyber And Electromagnetic Security Issues, George H. Baker
Electric Power: Cyber And Electromagnetic Security Issues, George H. Baker
George H Baker
Electric power is essential to the functioning of U.S. society. The electric power system increasingly operates at or near its reliability limits. The geographic scale of the tightly coupled networks involved makes the system susceptible to large-scale outages. More frequent natural and accidental failures portend possible catastrophes from intentional disruption. Deregulation has been a major factor to the lack of investment in system upgrades. Techniques to prevent attacks and reduce vulnerabilities are available and affordable.
Designing Resource-Bounded Reasoners Using Bayesian Networks: System Health Monitoring And Diagnosis, Ole J. Mengshoel
Designing Resource-Bounded Reasoners Using Bayesian Networks: System Health Monitoring And Diagnosis, Ole J. Mengshoel
Ole J Mengshoel
In this work we are concerned with the conceptual design of large-scale diagnostic and health management systems that use Bayesian networks. While they are potentially powerful, improperly designed Bayesian networks can result in too high memory requirements or too long inference times, to they point where they may not be acceptable for real-time diagnosis and health management in resource-bounded systems such as NASA’s aerospace vehicles. We investigate the clique tree clustering approach to Bayesian network inference, where increasing the size and connectivity of a Bayesian network typically also increases clique tree size. This paper combines techniques for analytically characterizing clique …
Markov Chain Monte Carlo Defect Identification In Nde Images, Aleksandar Dogandžić, Benhong Zhang
Markov Chain Monte Carlo Defect Identification In Nde Images, Aleksandar Dogandžić, Benhong Zhang
Aleksandar Dogandžić
We derive a hierarchical Bayesian method for identifying elliptically‐shaped regions with elevated signal levels in NDE images. We adopt a simple elliptical parametric model for the shape of the defect region and assume that the defect signals within this region are random following a truncated Gaussian distribution. Our truncated‐Gaussian model ensures that the signals within the defect region are higher than the baseline level corresponding to the noise‐only case. We derive a closed‐form expression for the kernel of the posterior probability distribution of the location, shape, and defect‐signal distribution parameters (model parameters). This result is then used to develop Markov …