Methodologies for reducing the design-space dimensionality in shape optimization have been recently developed based on unsupervised machine learning methods. These methods provide reduced representations of design space, capable maintaining a certain degree original variability. Nevertheless, they usually do not allow to use directly parameterization method, representing limitation their widesp...

Nowadays, one of the most important topics in risk management of banks, financial, and credit institutions is credit risk management. In this research, the researchers used survival analytic methods for credit risk modeling in terms of the conditional distribution function of default time. As a practical task, the authors considered the reward credit portfolio of Tose'e Ta'avon Bank of Guilan P...

A parametric model for the infrared signature caused by a buried land mine is presented. Further, a detector is calculated for the case where the background noise can be described by an autoregressive process. The detector separately estimates the parameters of the mine and the noise in an alternating fashion. The estimates are then used in the likelihood ratio test. Simulations show that signi...

This article considers Bayesian analysis of matched case-control problems when one of the covariates is partially missing. Within the likelihood context, the standard approach to this problem is to posit a fully parametric model among the controls for the partially missing covariate as a function of the covariates in the model and the variables making up the strata. Sometimes the strata effects...

background: although the cox proportional hazard regression is the most popular model for analyzing the prognostic factors on survival of cancer patients, under certain circumstances, parametric models estimate the parameter more efficiently than the cox model.  the aim of this study was to compare the cox regression model  with parametric models in patients with gastric cancer who registered a...

rational functions are of great interest to engineers and geoscientists. the rational polynomial coefficient (rpc) model as a generalized sensor model has been introduced as an alternative for the rigorous sensor model of the satellite imaging. numerical instability of normal equations is the only single obstacle to the implementation of these functions. practically, estimating rational functio...

DesignScript, as the name suggests, is positioned at the intersection of design and programming. DesignScript can be viewed as part of the continuing tradition of the development of parametric and associative modeling tools for advanced architectural design and building engineering. Much of the thought processes that contribute to the effective use of DesignScript builds on the tradition of par...

We describe a framework for robust kinematic design based on tolerance analysis and parametric design via configuration space manipulation. The input is a parametric model of a planar mechanical system comprised of lower and higher kinematic pairs in open or closed loops. The robust synthesis task is to find a nominal design that functions correctly despite small parameter variations. This task...

When you are assessing the quality of the evidence, it’s not how the data are analyzed that’s important. Far more important is how the data are collected. Don’t agonize over whether the researchers should have used a non-parametric test or whether a random effects meta-analysis is appropriate (just to cite two obscure examples). These are important issues and they generate a lot of debate. But ...