In a quantitative genetic investigation of seven clinical tests, five pairs were significantly correlated: (1) cover test measures and corneal power, (2) corneal power and divergence recovery points, (3) convergence and divergence recovery points, (4) divergence break and recovery points, and (5) convergence break and recovery points. Common genes may account entirely for the gene influence on ...

The primary objective of this work is to develop and test a new convergence acceleration technique we call multicloud. Multicloud is well-founded in the mathematical basis of multigrid, but relies on a meshless operator on coarse levels. The meshless operator enables extremely simple and automatic coarsening procedures for arbitrary meshes using arbitrary fine level discretization schemes. The ...

For the unsteady convection-diiusion equation in two dimensions we derive a new cell-based semi-discretization which is founded on the method of lines and a nite volume approach. Moreover, we present a second semidiscretization technique, a nonconforming Petrov-Galerkin method with exponentially tted trial and test functions. If we use appropriate quadrature rules both approaches are equivalent...

We have investigated variants of interval branch-and-bound algorithms for global optimization where the bisection step was substituted by the subdivision of the current, actual interval into many subintervals in a single iteration step. The convergence properties of the multisplitting methods, an important class of multisection procedures are investigated in detail. We also studied theoreticall...

We generalize the convergenece of an optimal semimeasure to a real probability in algorithmic probability by using game-theoretic probability theory and the theory of computable topology. Two lemmas in the proof give as corollary the existence of an optimal test and an optimal integral test, which are important from the point of view of algorithmic randomness. We only consider an SCT3 space, wh...

Particle filters are important approximation methods for solving probabilistic optimal filtering problems on nonlinear non-Gaussian dynamical systems. In this paper, we derive novel moment conditions for importance weights of sequential Monte Carlo based particle filters, which ensure the L convergence of particle filter approximations of unbounded test functions. This paper extends the particl...

We consider the fixed and exponential time-stepping Euler algorithms, with boundary tests, to calculate the mean first exit times (MFET) of two one-dimensional neural diffusion models, represented by the Ornstein–Uhlenbeck (OU) process and a stochastic space-clamped FitzHugh–Nagumo (FHN) system. The numerical methods are described and the convergence rates for the MFET analysed. A boundary test...

An interval global optimization method combined with the Direct Method for solving parametric linear systems is used for computing a tight enclosure for the solution set of parametric linear system whose input data are non-linear functions of interval parameters. Revised affine arithmetic is used to handle the nonlinear dependencies. The Direct Method performs the monotonicity test to speed up ...

In this paper, an immune genetic based algorithm (IGA) for random test pattern generation was proposed. Genetic algorithms (GA) solve many search and optimization problems, effectively. However, they may drop into local optimal solutions; or they may find the optimal solution by low convergence speed. To overcome these problems, we used the immune concept and GA algorithm for random-based test ...

 The concept of statistical convergence in $2$-normed spaces for double sequence was introduced in [S. Sarabadan and S. Talebi, {it Statistical convergence of double sequences  in $2$-normed spaces }, Int. J. Contemp. Math. Sci. 6 (2011) 373--380]. In the first, we introduce concept strongly statistical convergence in $2$-normed spaces and generalize some results. Moreover,  we define the conce...