The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

The production of power using the process of pressure–retarded osmosis (PRO) has been studied both experimentally and theoretically for simulated sea water vs. river water and deionized water under two cases: the first is for simulated real conditions of sea water and river water and second under low brine solution concentration to examine the full profile of the power- pressure. The influence of concentration polarization (CP) on water flux has been examined as well.

Oil flow lines are used to transport oil and its derivatives from a well over long distances, and because oil wells produce other potentially corrosive products, such as carbon dioxide and Hydrogen sulfide, it is necessary to take methods to protect the pipeline from corrosion. One of these methods is the use of corrosion inhibitors in this study. Prepare 5-acetyl-2-anilino-4-dimethylaminothiazole and test it as a corrosion inhibitor on a sample of the Rumaila flow line at a constant temperature 25°C in (3.5%) NaCl and (3.5%) KCl solution in the absence and presence of different concentrations of inhibitor (0 mM, 0.01 mM, 0.03 M, 0.05 mM). by using liner polarization (Tafel slope). The inhibiter exhibited the best performance at hi

   The main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits  of( FMOLP)   algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

This paper introduces some properties of separation axioms called α -feeble regular and α -feeble normal spaces (which are weaker than the usual axioms) by using elements of graph which are the essential parts of our α -topological spaces that we study them. Also, it presents some dependent concepts and studies their properties and some relationships between them.