The first half of the paper provides an overview of a new engineering software tool that is designed for the efficient solution of problems that may be modeled as systems of linear and nonlinear partial differential equations (PDEs) of parabolic type. Our tool is built upon the PARAMESH library, [15], which provides hierarchical mesh adaptivity in parallel in two and three dimensions. Our discr...

We consider the multispecies model described by a coupled system of diffusion–reaction equations, where coupling and nonlinearity are given in reaction part. construct semi-discrete form using finite volume approximation space. The fully implicit scheme is used for time, which leads to solving nonlinear equations at each time step. This paper presents two uncoupling techniques based on explicit...

A fully implicit finite difference scheme has been developed to solve the hydrodynamic equations coupled with radiation transport. Solution of the time dependent radiation transport equation is obtained using the discrete ordinates method and the energy flow into the Lagrangian meshes as a result of radiation interaction is fully accounted for. A tridiagonal matrix system is solved at each time...

Modelling and forecasting Stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. This nonlinearity affects the efficiency of the price characteristics. Using an Artificial Neural Network (ANN) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

objectives: cerebral hemispheres functioning have been found to be abnormal in children with asd. the role of lateralization in implicit and explicit motor learning has received little attention in asd researches. the main goal of this study is investigating the differences between two hands implicit and explicit motor learning in children with asd and typical matched group. methods: in the pre...

The geometric constraint enforcement using Lagrange Multipliers is one of the popular methods to control the behavior and trajectories of dynamically simulated entities. Therefore, effective and efficient enforcement and proper integration of the geometric constraints is the key to a successful constraint management. This paper describes the formulation and integration of geometric constraints ...

Time series prediction with neural networks has been the focus of much research in past few decades. Given recent deep learning revolution, there attention using models for time prediction, and hence it is important to evaluate their strengths weaknesses. In this paper, we present an evaluation study that compares performance multi-step ahead prediction. The methods comprise simple recurrent ne...