In this article, the nonlinear problem of Jeffery-Hamel flow has been solved analytically and numerically by using reliable iterative and numerical methods. The approximate solutions obtained by using the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM). The obtained solutions are discussed numerically, in comparison with other numerical solutions obtained from the fourth order Runge-Kutta (RK4), Euler and previous analytic methods available in literature. In addition, the convergence of the proposed methods is given based on the Banach fixed point theorem. The results reveal that the presented methods are reliable, effective and applicable to solve other nonlinear problems.

Given a matrix, the Consecutive Ones Submatrix (C1S) problem which aims to find the permutation of columns that maximizes the number of columns having together only one block of consecutive ones in each row is considered here. A heuristic approach will be suggested to solve the problem. Also, the Consecutive Blocks Minimization (CBM) problem which is related to the consecutive ones submatrix will be considered. The new procedure is proposed to improve the column insertion approach. Then real world and random matrices from the set covering problem will be evaluated and computational results will be highlighted.

This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance

Cognitive mapping in humans is the process of coding, storing, and processing information that. Can be used in special behavior . Several scientific Domains interfere in the concept of cognitive maps including cognitive Psychology and environmental Psychology. Three papers at the start of the last century introduced the concept of cognitive maps ,  ( Gulliverʼs  ,1908 ) brief note mentioned such maps in the context of teaching children orientation and there was a paper published by                ( Hutorowicz , 1911 ) comprising an abridged translation of a monograph written by ( B .F .Adler ) o

The aim of this study was to measure the effectiveness of a proposed program to develop the creative abilities of the students of Tabuk University and its impact on the creative output of the NEOM project. The sample of the study consisted of (50) university students divided into two groups: an experimental group of 25 students who receive the proposed training program, and control group of (25) students.

 To achieve these objectives, the researcher designed and developed tools to collect the required data, which were verified their validity and reliability.

The descriptive statistics of mean, standard deviations, correlation coefficient, T test for the associated sample were used in the analysis of the results of th

An ingrowing toenail is a common problem affecting mainly adolescents and young adults, with a male predominance of 3:1. The disorder generally occurs in big toes. It is painful and often chronic and it affects work and social activities. Most patients initially complain of pain and later discharge, infection and difficulty in walking occur. The Objectives: The purpose of the study was to evaluate the efficacy and safety of (10600nm) CO2 laser in the treatment of ingrowing toe nail. Patients, Materials & Methods: This study was done in laser medicine research clinics from July 2013 to the end of December 2013; 10 patients including 7(70%) males and 3 (30%) females with age ranging from 18 years to 70 years with mean age of 44 years o

In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.

The method of estimating the distribution parameters for each device was the OLS method.

The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and acc

Abstract

Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings