In this paper, we introduce a hybrid approach based on neural network and optimization teqnique to solve ordinary differential equation. In proposed model we use heyperbolic secont transformation function in hiden layer of neural network part and bfgs teqnique in optimization part. In comparison with existing similar neural networks proposed model provides solutions with high accuracy. Numerica...

In model-driven engineering, most problems are solved using model transformation. However, the development of a model transformation for a specific problem is still a hard task. The main reason for that is the lack of a development process where transformations must be designed before implemented. As in object-oriented design, we believe that “good design” of model transformation can benefit tr...

Background. Imagery ability is one of the most potent factors influencing imagery effectiveness. Therefore, prior to imagery training, it is important to assess the participant’s imagery ability, typically using a self-report questionnaire. Objectives. This study examined the factorial validity and internal consistency of the Malaysian adapted SIAQ using confirmatory factor analysis and Cronba...

Model transformation is one of the core techniques in ModelDriven Engineering. Many transformation languages exist nowadays, but few offer mechanisms directed to the reuse of whole transformations or transformation fragments in different contexts. Taking inspiration from generic programming, in this paper we define model transformation templates. These templates are not defined over concrete me...

This article proposes a taxonomy of model transformation, based on the discussions of a working group on model transformation of the Dagstuhl seminar on Language Engineering for ModelDriven Software Development. This taxonomy can be used, among others, to help developers in deciding which model transformation language or tool is best suited to carry out a particular model transformation activity.

The diversity of today’s model transformation languages makes it hard to compare their expressiveness and provide a framework for interoperability. Deconstructing and then re-constructing model transformation languages by means of a unique set of most primitive constructs facilitates both. We thus introduce T-Core, a collection of primitives for model transformation. Combining T-Core with a (pr...

Image classification and retrieval systems have gained more attention because of easier access to high-tech medical imaging. However, the lack of availability of large-scaled balanced labelled data in medicine is still a challenge. Simplicity, practicality, efficiency, and effectiveness are the main targets in medical domain. To achieve these goals, Radon transformation, which is a well-known t...