70 resultados para power graphs

em Cambridge University Engineering Department Publications Database


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We offer a solution to the problem of efficiently translating algorithms between different types of discrete statistical model. We investigate the expressive power of three classes of model-those with binary variables, with pairwise factors, and with planar topology-as well as their four intersections. We formalize a notion of "simple reduction" for the problem of inferring marginal probabilities and consider whether it is possible to "simply reduce" marginal inference from general discrete factor graphs to factor graphs in each of these seven subclasses. We characterize the reducibility of each class, showing in particular that the class of binary pairwise factor graphs is able to simply reduce only positive models. We also exhibit a continuous "spectral reduction" based on polynomial interpolation, which overcomes this limitation. Experiments assess the performance of standard approximate inference algorithms on the outputs of our reductions.

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A mathematical model of the transport of sedimented solids within a decanter centrifuge has been developed. The primary purpose of the model is to calculate the power, torque and axial force required for the scroll to transport the solids along the bowl. The model is presented in a non-dimensional form and the procedure for implementing the model is included. The model is compared to test data from an existing publication; there was good agreement between the model and data. Example results are presented in the form of graphs to illustrate the influence of key parameters. © 2013 Elsevier Ltd.

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In this paper, micro gas sensor was fabricated using indium oxide nanowire for effective gas detection and monitoring system. Indium oxide nanowire was grown using thermal CVD, and their structural properties were examined by the SEM, XRD and TEM. The electric properties for microdropped indium oxide nanowire device were measured, and gas response characteristics were examined for CO gas. Sensors showed high sensitivity and stability for CO gas. And with below 20 mw power consumption, 5 ppm CO could be detected.