The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The developed ANN mode gave a high correlation coefficient reaching 0.927 for the prediction of TDS from the model and showed high levels of TDS in Al-Hawizeh marsh that pose threats to people using the marsh for drinking and other uses. The dissolved Oxygen concentration has the highest importance of 100% in the model because the water of the marsh is fresh water, while Turbidity had the lowest importance.
The application of ultrafiltration (UF) and nanofiltration (NF) processes in the handling of raw produced water have been investigated in the present study. Experiments of both ultrafiltration and nanofiltration processes are performed in a laboratory unit, which is operated in a cross-flow pattern. Various types of hollow fiber membranes were utilized in this study such as poly vinyl chloride (PVC) UF membrane, two different polyether sulfone (PES) NF membranes, and poly phenyl sulfone PPSU NF membrane. It was found that the turbidity of the treated water is higher than 95 % by using UF and NF membranes. The chemical oxygen demand COD (160 mg/l) and Oil content (26.8 mg/l) were found after treatment according to the allowable limits set
... Show MoreBackground: Toxin-producing Shiga Escherichia coli has been identified as a new foodborne pathogen that poses a significant health risk to humans. Shiga toxin-producing Escherichia coli can be found in raw cow milk and its derivatives. A small number of Escherichia coli strains that produce shiga toxin are pathogenic. Aim of study: The study aimed to see if there were any virulence genes in 50 milk samples that were typical of Entero-haemorrhagic E. coli and evaluate the Myrtus communis effects on these bacteria. Materials and Method: Milk samples were used to isolate E. coli bacteria (n= 27), biochemically analyzed, and genetically screened for virulence genes using a multiplex (PCR). The hydro-alcoholic extraction of Myrtus communis leave
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The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storag
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
... Show MoreThe specific activity of 29 soil samples collected from Fuel
Fabrication Facility FFF at AL-Tuwaitha site, 20 km south of
Baghdad were determined using HPGe detector in a low background
configuration, it's relative efficiency of 40%, and resolution of 2keV
for the 1332 keV gamma ray emission of 60Co. The range of activity
concentrations of 226Ra, 232Th and 40K were between (12.56-31.96),
(10.2-18.4) and (47.47-402.1) Bq/kg respectively. In order to assess
any radiological hazard to human health, the absorbed gamma dose
rate D in air at 1m above the ground surface was calculated in the
range (18.87 to 36.46) nGy/h; the outdoor annual effective dose
equivalent AEDE was evaluated to vary from 0.0039 to 0.0076
The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
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Background: Knowing the indications for a cesarean section will help to have a better understanding of this common obstetrical procedure and prepare for the high level of care management that it entails. Aims of the study: The goal of this study was to determine the factors that influence caesarean section indications among women who visited AL-Dewaniya Maternity and Pediatric Hospital, as well as the relationship between caesarean section women's indications and socio-demographic data. Methodology: A descriptive cross-sectional study design is conducted for the period of December 26th 2020 to June 1st 2021 at Al Dewaniya Maternity and Pediatric Hospital. The validity of the questionnaire is determined through a panel of experts and reliabi
... Show MoreThree cohesionless free flowing materials of different density were mixed in an air fluidized bed to study the mixing process by calculating performance of mixing index according to Rose equation (1959) and to study the effect of four variables (air velocity, mixing time, particle size of trace component and concentration of trace component) on the mixing index and as well as on mixing performance. It was found that mixing index increases with increasing the air velocity, mixing time and concentration of trace component until the optimum value. Mixing index depends on the magnitude of difference in particle size The first set of experiments (salt then sand then cast iron) give higher mixing index and better performance of mixing than the
... Show MoreElectrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on
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