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ObjectiveTo construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure. MethodsThis study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) ...
The important task of evaluating the impact of random parameters on the output of stochastic ordinary differential equations (SODE) can be computationally very demanding, in particular for problems with a high-dimensional parameter space. In this work we c ...
Seeking to develop efficient and accurate absorbing layers for the low-speed weakly compressible Navier-Stokes equations, we exploit the connection to the BGK-approximation to develop an absorbing layer with qualities similar to that of the perfectly match ...
A new approach is proposed to detect edges based on an artificial neural network (ANN). Some elementary continuous and discontinuous functions interpolated in the polynomial space and their continuity are used as the training sets to train a back propagati ...
We discuss adaptive sparse grid algorithms for stochastic differential equations with a particular focus on applications to electromagnetic scattering by structures with holes of uncertain size, location, and quantity. Stochastic collocation (SC) methods a ...
The classic Lebesgue ANOVA expansion offers an elegant way to represent functions that depend on a high-dimensional set of parameters and it often enables a substantial reduction in the evaluation cost of such functions once the ANOVA representation is con ...
