BACKGROUND This study compared the methodological requirements for early health technology appraisal (HTA) by the Federal Joint Committee/Institute for Quality and Efficiency in Health Care (G-BA/IQWiG; Germany) and the National Institute for Health and Care Excellence (NICE; England). METHODS The following aspects were examined: guidance texts on methodology and information sources for the a...

The cryogenic cavitation has critical implications on the performance and safety of liquid rocket engines. In this study, a systematic investigation based on the surrogate modeling techniques is conducted to assess and improve the performance of a transport-based cryogenic cavitation model. Based on the surrogate model, global sensitivity analysis is be conducted to assess the role of model par...

s:1640:"Background: Surrogacy is one of the most controversial procedures in infertility treatment. Despite increasing of using this technology in Iran, there are few practical data about surrogacy. There isn't any study assessing experiences of commissioning mothers about surrogate mother selection. The purpose of this study was exploring of commissioning mothers' experiences in sele...

In this paper, an optimization approach was presented for the flexural strength and stiffness design of reinforced concrete beams. Surrogate modeling based on machine learning applied to predict responses structural system in three-point flexure tests. Three input variables, area steel bars compression zone, tension shear were adopted dataset arranged by Box-Behnken method. The composed thirtee...

For the design and optimization of multistage assembly processes, a computationally cheap mathematical model that links design parameters with the final product dimensional quality is highly desirable. We propose a systematic approach to building a surrogate model of simulations of multistage assembly processes. At the heart of this approach is a multiple-input-multiple-output surrogate modelin...

Optimization of nonlinear (or linear state-dependent) dynamic systems often requires system simulation. In many cases the associated state derivative evaluations are computationally expensive, resulting in simulations that are significantly slower than real-time. This makes the use of optimization techniques in the design of such systems impractical. Optimization of these systems is particularl...

Nonlinear modeling routines are often applied in an effort to extract underlying determinism from time series data. The best of these methods perform well for short noisy time series when there is determinism in the underlying system. We show that nonlinear modeling does not distinguish between a static nonlinear transformation of linearly filtered noise and dynamic nonlinearity. To relieve thi...

We propose a semiparametric Bayesian method for handling measurement error in nutritional epidemiological data. Our goal is to estimate nonparametrically the form of association between a disease and exposure variable while the true values of the exposure are never observed. Motivated by nutritional epidemiological data, we consider the setting where a surrogate covariate is recorded in the pri...