Our aim was to investigate the changes in the myocardium stiffness index for patients suffering from systemic hypertension, and to assess their left ventricular performance. We studied 263 hypertensive patients and 166 healthy subjects as a control group. By using conventional Doppler echocardiography, the following parameters were measured—Left ventricular end diastolic diameter, left ventricular end systolic diameter, transmitral early velocity, isovolumic relaxation time, and isovolumic contraction time. Tissue Doppler imaging (TDI) was used in the measurements of the early mitral annular velocity (Ea) and the diastolic stiffness was obtained by calculating the ratio E\Ea\LVIDd. Index myocardial performance (IMP) was calculated

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

Abstract. This study presents experimental and numerical investigation on the effectiveness of electrode geometry on flushing and debris removal in Electrical Discharge Drilling (EDD) process. A new electrode geometry, namely side-cut electrode, was designed and manufactured based on circular electrode geometry. Several drilling operations were performed on stainless steel 304 using rotary tubular electrodes with circular and side-cut geometries. Drilling performance was characterized by Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Tool Wear Ratio (TWR). Dimensional features and surface quality of drilled holes were evaluated based on Overcut (OC), Hole Depth (HD), and Surface Roughness (SR). Three-dimensional

This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load at different operating frequencies. The effect of relative density, depth of embedment, foundation area as well as the imposed harmonic load was investigated. It was found that the amplitude of displacement of the foundation increases with increasing the amplitude of dynamic force and operating frequency meanwhile it decreases with increasing the relative density of sand, degree of saturation, depth of embedment and contact area of footing. The maximum displacement was noticed at 33.34 to 41.67 Hz. The maximum displacement amplitude respons

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load at different operating frequencies. The effect of relative density, depth of embedment, foundation area as well as the imposed harmonic load was investigated. It was found that the amplitude of displacement of the foundation increases with increasing the amplitude of dynamic force and operating frequency meanwhile it decreases with increasing the relative density of sand, degree of saturation, depth of embedment and contact area of footing. The maximum displacement was noticed at 33.34 to 41.67 Hz. The maximum displaceme

Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method

In an earlier paper, the basic analytical formula for particle-hole nuclear state densities was derived for non-Equidistant Spacing Model (non-ESM) approach. In this paper, an extension of the former equation was made to include pairing. Also a suggestion was made to derive the exact formula for the particle-hole state densities that depends exactly on Fermi energy and nuclear binding energies. The results indicated that the effects of pairing reduce the state density values, with similar dependence in the ESM system but with less strength. The results of the suggested exact formula indicated some modification from earlier non-ESM approximate treatment, on the cost of more calculation time

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve