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

The experimental and numerical analysis was performed on pipes suffering large plastic deformation through expanding them using rigid conical shaped mandrels, with three different cone angles (15◦, 25◦, 35◦) and diameters (15, 17, 20) mm. The experimental test for the strain results investigated the expanded areas. A numerical solution of the pipes expansion process was also investigated using the commercial finite element software ANSYS. The strains were measured for each case experimentally by stamping the mesh on the pipe after expanding, then compared with Ansys results. No cracks were generated during the process with the selected angles. It can be concluded that the strain decreased with greater angles of con

Animation is an industry that is expanding more quickly than ever. Every child’s favorite activity is watching cartoons. Therefore, it is essential to be cautious of the kinds of cartoon films children and teenagers tend. Because children and teenagers are the target audience for these films. This study aims at exposing a hidden enactment, namely racism, in a well-known cartoon film, Lion King, which has been selected accurately by the researchers because it shapes a set of ideas about black people and constructs prejudiced beliefs in their minds. This study is to answer the inquiry ‘Is the ideology of racism imposed in Lion King? And how?’ The significance of the present paper lies in highlighting the educational function of

Cystic fibrosis (CF) is an autosomal recessive multisystem disease that results from mutation(s) of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. More than 2100 mutations and polymorphisms have been reported in this gene so far. Incidence and genotyping of CF are under-identified in Iraq. This study aims to determine the types and frequencies of certain CFTR mutations among a sample of Iraqi CF patients. Two groups of patients were included: 31 clinically confirmed CF patients in addition to 47 clinically suspected patients of CF. All confirmed pa

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 twentyfour 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.

The Halabja earthquake occurred on 12/11/2017 in Iraq, with a magnitude of 7.3 Mw, which happened in the Iraqi-Iranian borders. This earthquake killed and injured many people in the Kurdish region in the north of the country. There is no natural disaster more dangerous than earthquake, especially it occurs without warning, great attention must be paid to the impact of earthquakes on the soil and preparing for a wave of earthquakes. Numerical modeling using specific elements is considered a powerful tool to investigate the required behavior of structures in Geotechnical engineering, and the main objective of this is to assess the response of the Al-Wand dam to the Halabja earthquake, as this dam is located in an area that has been su

The applications of Multilevel Converter (MLC) are increased because of the huge demand for clean power; especially these types of converters are compatible with the renewable energy sources. In addition, these new types of converters have the capability of high voltage and high power operation. A Nine-level converter in three modes of implementation; Diode Clamped-MLC (DC-MLC), Capacitor Clamped-MLC (CC-MLC), and the Modular Structured-MLC (MS-MLC) are analyzed and simulated in this paper. Various types of Multicarrier Modulation Techniques (MMTs) (Level shifted (LS), and Phase shifted (PS)) are used for operating the proposed Nine level - MLCs. Matlab/Simulink environment is used for the simulation, extracting, and ana

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve