BACKGROUND To evaluate the accuracy of transvaginal ultrasonography (TVS) for the detection of ectopic pregnancies (EPs) in women undergoing surgery for presumed ectopic pregnancy. METHODS A prospective, observational study. Women were diagnosed with an EP using TVS if any of the following were noted in the adnexal region: (i) an inhomogeneous mass or blob sign adjacent to the ovary and movin...

This paper considers a nonparametric varying coefficient regression model with longitudinal dependent variable and cross-sectional covariates. The relationship between the dependent variable and the covariates is assumed to be linear at a specific time point, but the coefficients are allowed to change over time. Two kernel estimators based on componentwise local least squares criteria are propo...

kernel density estimators are the basic tools for density estimation in non-parametric statistics.  the k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in  which  the  bandwidth  is varied depending on the location of the sample points. in this paper‎, we  initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...

In this letter, the numerical scheme of nonlinear Volterra-Fredholm integro-differential equations is proposed in a reproducing kernel Hilbert space (RKHS). The method is constructed based on the reproducing kernel properties in which the initial condition of the problem is satised. The nonlinear terms are replaced by its Taylor series. In this technique, the nonlinear Volterra-Fredholm integro...

The traditional method in Iran of cracking walnut manually, using harmer or knife cutter is laborintensive, slow and tedious; besides, most mechanical crackers do not give satisfactory results in terms of kernel extraction quality. A prototype machine was developed to crack walnut. A walnut cracker was designed, constructed and tested to evaluate its performance. The cracker, which consists of ...

Kernel theory is a demonstrated tool that has made its way into nearly all areas of machine learning. However, serious limitation kernel methods knowing which needed in practice. Multiple learning (MKL) an attempt to learn new tailored through the aggregation set valid known kernels. There are generally three approaches MKL: fixed rules, heuristics, and optimization. Optimization most popular; ...

in this paper, we introduce the notion of an action $y_x$as a generalization of the notion of a module,and the notion of a norm $vt: y_xto f$, where $f$ is a field and $vartriangle(xy)vartriangle(y') =$ $ vartriangle(y)vartriangle(xy')$ as well as the notion of fuzzy norm, where $vt: y_xto [0, 1]subseteq {bf r}$, with $bf r$  the set of all real numbers. a great many standard mappings on algebr...

on the basis of a reproducing kernel space, an iterative algorithm for solving the one-dimensional linear and nonlinear schrödinger equations is presented. the analytical solution is shown in a series form in the reproducing kernel space and the approximate solution is constructed by truncating the series. the convergence of the approximate solution to the analytical solution is also proved. th...