In this paper, we define a new subclass of multivalent functions defined by the generalized integral operator with negative coefficients in the open unit disk U. We also give and study some interesting properties such as coefficient estimates, subordination theorems and integral means inequalities by using the famous Littlewood's subordination theorem. Finally, we conclude a type of inequalities that is upper bound and lower bound for topology multivalent functions of all analytic functions.  

The concept of epiform modules is a dual of the notion of monoform modules. In this work we give some properties of this class of modules. Also, we give conditions under which every hollow (copolyform) module is epiform.

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

Background : Gallstone disease is one of a common surgical problem and one of the most common gastrointestinal diseases throughout the world but its pathogenesis remains unclear. Many theories have been put forward to explain the mechanism of stone formation. The living organism has enzymatic and non-enzymatic antioxidant systems neutralizing the harmful effects of the endogenous oxygen free radicals products. Under certain conditions, the oxidative or anti-oxidative balance shifts towards the oxidative status as a result of increase in oxygen free radicals and/or impairment in antioxidant mechanism.

Objective :To evaluate the oxidative stress markers (total antioxidants capacity and malondialdeh

Medical image segmentation is a frequent processing step in image medical understanding and computer aided diagnosis. In this paper, development of range operator in image segmentation is proposed depending on dermatology infection. Three different block sizes have been utilized on the range operator and the developed ones to enhance the behavior of the segmentation process of medical images. To exploit the concept of range filtering, the extraction of the texture content of medical image is proposed. Experiment is conducted on different medical images and textures to prove the efficacy of our proposed filter was good results.