The wide use of lead compounds as an engine anti-knock reflects conversely on all components of the ecosystem. This study aimed to detect the concentration of lead in various types of gasoline and gas oil that are highly consumed by vehicles. Eight fuel samples were collected from different feul stations distributed in different districts of Baghdad city. These included two gas oil (diesel) stations and three stations for each type of gasoline (leaded and unleaded). Lead was extracted by the modified chemical method, and then flame atomic absorption technique was applied to assay its concentrations. The results indicated that lead levels were within permitted limits (150 mg Lead L^-1) recommended by the

Face recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o

Noor Oil Field is one of Iraqi oil fields located in Missan province / Amarah city. This field is not subjected to licensing rounds, but depends on the national effort of  Missan Oil Company. The first two wells in the field were drilled in seventies and were  not opened to production until 2009. The aim of this study is to study the possibility of using the method of gas lift to increase the productivity of this field . PROSPER software was used to design the continuous  gas lift by using maximum production rate in the design.

   The design was made after comparing  the measured pressure with the calculated pressure, this comparison  show  that the method of Beggs-Brill and Petroleum Exper

     As a result of the pandemic crisis and the shift to digitization, cyber-attacks are at an all-time high in the modern day despite good technological advancement. The use of wireless sensor networks (WSNs) is an indicator of technical advancement in most industries. For the safe transfer of data, security objectives such as confidentiality, integrity, and availability must be maintained. The security features of WSN are split into node level and network level. For the node level, a proactive strategy using deep learning /machine learning techniques is suggested. The primary benefit of this proactive approach is that it foresees the cyber-attack before it is launched, allowing for damage mitigation. A cryptography algorithm is put

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

This research aimed to predict the permanent deformation (rutting) in conventional and rubberized asphalt mixes under repeated load conditions using the Finite Element Method (FEM). A three-dimensional (3D) model was developed to simulate the Wheel Track Testing (WTT) loading. The study was conducted using the Abaqus/Standard finite element software. The pavement slab was simulated using a nonlinear creep (time-hardening) model at 40°C. The responses of the viscoplastic model under the influence of the trapezoidal amplitude of moving wheel loadings were determined for different speeds and numbers of cycles. The results indicated that a wheel speed increase from 0.5Km/h to 1.0Km/h decreased the rut depth by about 22% and 24% in conv

      In this article, a numerical study of compressible and weak compressible Newtonian flows is achieved for a time marching, Galerkin algorithm. A comparison between two numerical techniques for such flows, namely the artificial compressibility method (AC–method) and the fully artificial compressibility method (FAC–method) is performed. In the first artificial compressibility parameter (  is added to the continuity equation, while this parameter is added to both continuity and momentum equations in the second technique. This strategy is implemented to treat the governing equations of Newtonian flow in cylindrical coordinates (axisymmetric). Particularly, this study concerns with the effect of the artificial compressibility p