Accurate computation of Mathieu functions

This lecture presents a modern approach for the computation of Mathieu functions. These functions find application in boundary value analysis such as electromagnetic scattering from elliptic cylinders and flat strips, as well as the analogous acoustic and optical problems, and many other applications in science and engineering. The authors review the traditional approach used for these functions, show its limitations, and provide an alternative ""tuned"" approach enabling improved accuracy and convergence. The performance of this approach is investigated for a wide range of parameters and mac

Predicting haz hardness with artificial neural networks

The use of artificial neural networks (backpropagation networks) for predicting heat-affected zone hardness. given the 800-500 C cooling time and chemical composition, is investigated in this study. The experimental training data are taken from a database assembled by Yurioka et al. Network predicted hardness values are compared with experimental values from the entire Yurioka database and reasonable agreement is found (correlation factor = 0.98). The network results are also compared with values calculated from the regression relationships of Yurioka and Suzuki based on the same database. Finally, an optimal network architecture (1 hidden layer. 4 hidden nodes and 40 training patterns) is suggested

Nutrition care process model approach to surgical prehabilitation in oncology

The nutrition care process is a standardized and systematic method used by nutrition professionals to assess, diagnose, treat, and monitor patients. Using the nutrition care process model, we demonstrate how nutrition prehabilitation can be applied to the pre-surgical oncology patient.</p