let $c$ be a nonempty closed convex subset of a real hilbert space $h$. let ${s_n}$ and ${t_n}$ be sequences of nonexpansive self-mappings of $c$, where one of them is a strongly nonexpansive sequence. k. aoyama and y. kimura introduced the iteration process $x_{n+1}=beta_nx_n+(1-beta_n)s_n(alpha_nu+(1-alpha_n)t_nx_n)$ for finding the common fixed point of ${s_n}$ and ${t_n}$, where $uin c$ is ...

To find an optimum accelerating parameter of the SOR method is important and a difficult part of the problem. It is more difficult to estimate many optimum parameters of the GSOR method. In this talk, we propose a new algorithm to estimate the optimum parameters of the GSOR method. The key point to estimate these parameters is using a preconditioned matrix constructed by a part of the coefficie...

In this paper, we present a novel robust method for point matching under noise, deformation, occlusion and outliers. We introduce a new probability model to represent point sets, namely asymmetric Gaussian (AG), which can capture spatially asymmetric distributions. Firstly, we use a mixture of AGs to represent the point set. Secondly, we use L2-minimizing estimate (L2E), a robust estimator to e...

For iteration sequences otherwise converging linearly, the proposed one-point extrapolation method attains a convergence rate and efficiency of 1.618. This is accomplished by retaining an estimate of the linear coefficient from the previous step and using the estimate to extrapolate. For linear convergence problems, the classical Aitken-Steffensen 6 -process has an efficiency of just -J2, while...

A cross-sectional study evaluated 182 students in the last two years of medical school and 70 residents of a national hospital in Peru on the risk indicators used for reporting results in clinical trials. A questionnaire was used to assess the ability to recognize and calculate risk indicators most widely used in the epidemiological literature. From the participants, 19.4% did not recognize any...