The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Due to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.

In this paper, new concepts which are called: left derivations and generalized left derivations in nearrings have been defined. Furthermore, the commutativity of the 3-prime near-ring which involves some
algebraic identities on generalized left derivation has been studied.

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

  Let L be a commutative ring with identity and let W be a unitary left L- module. A submodule D of an L- module W is called  s- closed submodule denoted by  D ≤sc W, if D has   no  proper s- essential extension in W, that is , whenever D ≤ W such that D ≤se H≤ W, then D = H. In  this  paper,  we study  modules which satisfies  the ascending chain  conditions (ACC) and descending chain conditions (DCC) on this kind of submodules.

This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB )  to find the optimal solution

A numerical method for the calculation of the three-dimensional wake rollup behind symmetric wings with ground effect and its aerodynamic characteristics for steady low subsonic flow have been developed. A non-planar quadrilateral vortex-ring method with vortex wake relaxation iterative scheme for lifting surfaces is obtained. A computer program was build to treat wings with breaks, span wise trailing edge flaps, local dihedral angle, camber, twist and ground effect. Forces and moments are obtained from vector product of local velocity and vortex strength multiplied by density. The program has been validated for a number of configurations for which experimental data is available. Good agreement has been obtained for these configurations. Al

In this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data  sets