Water injection equipments such as pipelines, which are used in the second recovery of oil in the Al-Ahdeb wells, suffer from the corrosion in water during maintaining vacuum deoxygenated tower that used to decrease concentration of the dissolved oxygen gas in the water from 6.2-9.1 ppm to o.5 ppm. This study involved calculation the corrosion rates of the internal surfaces of the
pipelines either during operation of the vacuum unit or when the tower out of operation. Finally, find the solution by one of the following suggestions. In the first suggestion removal of the dissolved O2 from water is achieved by increasing the dosage of the oxygen scavenger (sodium sulphite). The second suggestion involves removing the dissolved O2 from w

Water injection equipments such as pipelines, which are used in the second recovery of oil in the Al-Ahdeb wells, suffer from the corrosion in water during maintaining vacuum deoxygenated tower that used to decrease concentration of the dissolved oxygen gas in the water from 6.2-9.1 ppm to o.5 ppm. This study involved calculation the corrosion rates of the internal surfaces of the pipelines either during operation of the vacuum unit or when the tower out of operation.  Finally, find the solution by one of the following suggestions. In the first suggestion removal of the dissolved O₂ from water is achieved by increasing the dosage of the oxygen scavenger (sodium sulphite). The second suggestion involves re

Erbil city is located in the northern Iraq with a population of over one million people. Due to water crises farmers usually use wastewater and well water for the agricultural production. In this study six stations were designed to sample waste water and three from well water to define waste water and ground water characteristics. In this study, Residual Na⁺ Carbonate, Mg⁺⁺ hazard, salinity hazard, Kelley index, %sodium, total hardness, permeability index, potential salinity, sodium adsorption ratio, and Irrigation Water Quality Index (IWQI) were determined. The order of average cation concentrations in water was Mg²⁺> Ca²⁺ > Na⁺ > K⁺. While the proportion of main

Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia applications. To

Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia appli

Sewage water is a mixture of water and solids added to water for various uses, so it needs to be treated to meet local or global standards for environmentally friendly waste production. The present study aimed to analyze the new Maaymyrh sewage treatment plant's quality parameters statistically at Hilla city. The plant is designed to serve 500,000 populations, and it is operating on a biological treatment method (Activated Sludge Process) with an average wastewater inflow of 107,000m³/day. Wastewater data were collected daily by the Mayoralty of Hilla from November 2019 to June 2020 from the influent and effluent in the (STP) new in Maaymyrh for five water quality standards, such as (BOD5), (COD), (TSS), (TP)

Abstract To ensure that the distribution system has safe drinking water. It is necessary to know the residual chlorine concentrations at various points in the network. A chlorine photometer device was used to measure twenty points taken every day for a week at a selected time in the distribution system. Both pressures and flows in the network were measured using bourdon gauge and Tuf-2000H Handheld Digital ultrasonic flow meters. WaterGEMS CONNECT Edition update one software was used to simulate the flow in the network. The Baghdad water department provided the data about the network, such as the lengths of pipes, the layout of the network, and pipes diameters. The network calibrated consists of 781 pipes of different lengths and 542 juncti

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par