A time advance strategy for cyclic loading will be presented, applied to the fatigue formulation first proposed by [1]. The coupling of both formulations provides a comprehensive approach to simulate high cycle fatigue problems accurately and with an important computational cost reduction. The capabilities of the proposed procedure are shown in a numerical example.

Nutrient input to the Laurentian Great Lakes continues to cause problems with eutrophication. To reduce the extent and severity of these problems, target nutrient loads were established and Total Maximum Daily Loads are being developed for many tributaries. Without detailed loading information it is difficult to determine if the targets are being met and how to prioritize rehabilitation efforts...

Visual interpolation between dots responsible for rectilinear versus curvilinear contour interpretation was examined with the psychophysical forced directional response (FDR) paradigm. Regular four-dot polygon segments, together with a target dot, were presented to the subjects for 150 ms. Subjects were required to indicate the direction of deviation of the target dot from the midpoint of the i...

premature chromosome condensation (pcc) appears to have a possible utility for biological dosimetry purposes. the pcc technique may be adapted for cases of suspicion of overexposure where sampling is performed at least one day after an accident. for this purpose, human blood samples were exposed in vitro to 60co up to 10 gy and the pcc technique was performed immediately after irradiation. anal...

Consider the online regression problem where the dependence of the outcome yt on the signal xt changes with time. Standard regression techniques, like Ridge Regression, do not perform well in tasks of this type. We propose two methods to handle this problem: WeCKAAR, a simple modification of an existing regression technique, and KAARCh, an application of the Aggregating Algorithm. Empirical res...

A new regression technique based on Vapnik’s concept of support vectors is introduced. We compare support vector regression (SVR) with a committee regression technique (bagging) based on regression trees and ridge regression done in feature space. On the basis of these experiments, it is expected that SVR will have advantages in high dimensionality space because SVR optimization does not depend...

In this article, we propose applying a recently proposed technique of reducing Support Vector Classification models for regression problems. The reduced method creates reduced models by removing support vectors and uses a general formulation of Support Vector Classification with a priori knowledge in the form of detractors. We apply this method for regression problems by using a reformulation o...

ABSTRACT A novel technique is presented to construct sparse Gaussian regression models. Unlike most kernel regression modelling methods, which restrict kernel means to the training input data and use a fixed common variance for all the regressors, the proposed technique can tune the mean vector and diagonal covariance matrix of individual Gaussian regressor to best fit the training data based o...