In the present work a dynamic analysis technique have been developed to investigate and characterize the quantity of elastic module degradation of cracked cantilever plates due to presence of a defect such as surface of internal crack under free vibration. A new generalized technique represents the first step in developing a health monitoring system, the effects of such defects on the modal frequencies has been the main key quantifying the elasticity modulii due to presence any type of un-visible defect. In this paper the finite element method has been used to determine the free vibration characteristics for cracked cantilever plate (internal flaws), this present work achieved by different position of crack. Stiffness re

he aim of the research is to clarify the meanings and connotations of (Semitic), and to identify the peoples that fell under this name according to historical data, biblical texts and Qur’anic news. International sympathy on the one hand and on the other hand controlling the land of Palestine and giving them international legitimacy to grow their entity according to global support and sympathy with their alleged slogan (anti-Semitism), which revolves around the oppression of the Jews.

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

In this work, the spectra of plasma glow produced by Nd:YAG laser operated at 1.064 μm on Al-Mg alloys with same molar ratio samples in air were analyzed by comparing the atomic lines of aluminum and magnesium with that of strong standard lines. The effect of laser energies on spectral lines, produced by laser ablation, were investigated using optical spectroscopy, the electron density was measured utilizing the Stark broadening of magnesium-aluminum lines and the electron temperature was calculated from the standard Boltzmann plot method. The results that show the electron temperature increases in magnesium and aluminum targets but decreases in magnesium: aluminum alloy target, also show the electron density increase all the aluminum,

Objective of the study was to rate and analyze the physical fitness of female students from Iraq and Russia to find similarities, differences and regularities. Sampled for the study were 44 female non-sporting students: 20 students from Pedagogical University in Bagdad; and 24 students from Russian State University of Physical Education, Sport, Youth and Tourism in Moscow. The study was designed to obtain the joints flexibility, coordination, speed-strength and static endurance rates. The Iraqi students were tested with higher coordination abilities than their Russian peers, whilst the latter were ranked higher in the speed-strength, shoulder joints and spine flexibility tests, albeit lower than their Iraqi peers in the hip flexibility test

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation