In this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A comparison between numerical and experimental data, illustrated

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.

This study explores the language used in reporting political headlines conducting a rhetorical stylistic analysis. It is based on showing the effect of the rhetorical stylistic relations in news reporting. The aim is to investigate the structure adopted in reporting political news. It argues that the rhetorical stylistic devices are necessary and applicable to non-literary texts, i.e. political headlines to evaluate language use in the representation of non-literary texts. The analysis was carried out on data selected from the British broadsheet The Guardian and the American New York Times newspaper headlines. The data were examined and subjected to a contrastive analysis incorporating rhetorical and stylistic tools to discern h

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 influence of Cr3+ doping on the ground state properties of SrTiO3 perovskite was evaluated using GGA-PBE approximation. Computational modeling results infered an agreement with the previously published literature. The modification of electronic structure and optical properties due to Cr3+ introducing into SrTiO3 were investigated. Structural parameters assumed that Cr3+ doping alters the electronic structures of SrTiO3 by shifting the conduction band through lower energies for the Sr and Ti sites. Besides, results showed that the band gap was reduced by approximately 50% when presenting one Cr3+ atom into the SrTiO3 system and particularly positioned at Sr sites. Interestingly, substituting Ti site by Cr3+ led to eliminating the band ga

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

The bit record is a part from the daily drilling report which is contain information about the type and the number of the bit that is used to drill the well, also contain data about  the used weight on bit  WOB ,revolution per minute RPM , rate of penetration ROP, pump pressure ,footage drilled and bit dull grade. Generally we can say that the bit record is a rich brief about the bit life in the hole. The main purpose of this research is to select the suitable bit to drill the next oil wells because the right bit selection avoid us more than one problems, on the other hand, the wrong bit selection cause more than one problem. Many methods are related to bit selection, this research is familiar with four of thos