Introduction: For the past 7 years, a nursing school has conducted biannual medical missions in a virtually inaccessible area in Haiti. Each medical mission team provides primary care, pediatric and gynecological examinations for up to 6 days in the impoverished island nation. Methods: To improve the safety of participants engaged in this humanitarian tra...

Background: The practice of 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. Aim: The purpose of this study was exploring of commissioning mothers' experiences in se...

Surrogate-based optimization (Queipo et al. 2005, Simpson et al. 2008) represents a class of optimization methodologies that make use of surrogate modeling techniques to quickly find the local or global optima. It provides us a novel optimization framework in which the conventional optimization algorithms, e.g. gradient-based or evolutionary algorithms are used for sub-optimization(s). Surrogat...

A reduced-order nonlinear unsteady aerodynamic modeling approach suitable for analyzing pitching/plunging airfoils subject to fixed or time-varying freestream Mach numbers is described. The reduced-order model uses kriging surrogates to account for flow nonlinearities and recurrence solutions to account for time-history effects associated with unsteadiness. The resulting surrogate-based recurre...

Expectation-maximization (EM) is an iterative algorithm for finding the maximum likelihood or maximum a posteriori estimate of the parameters of a statistical model with latent variables or when we have missing data. In this work, we view EM in a generalized surrogate optimization framework and analyze its convergence rate under commonly-used assumptions. We show a lower bound on the decrease i...

This paper focuses upon the efficient surrogate model algorithm for expensive simulation-based design optimization problems. Co-kriging method is used to develop a multi-fidelity surrogate model using two independent datasets. To achieve this objective, wing-body problem is taken as an example of application for highdimensional complex design problem. In addition, a simple sampling analysis is ...

customer knowledge management (ckm) has been a subject of much attention in recent years. the attractiveness of this subject is the result of its benefits for organizations; but despite the benefits of ckm implementation, many projects aimed at implementing ckm in organizations fail due to companies’ negligence with respect to its implementation factors. meanwile the majority of organizations u...

We establish a general correspondence between two classes of statistical functions: AliSilvey distances (also known as f -divergences) and surrogate loss functions. Ali-Silvey distances play an important role in signal processing and information theory, for instance as error exponents in hypothesis testing problems. Surrogate loss functions (e.g., hinge loss, exponential loss) are the basis of ...