Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and the water quality index used to assess the quality of water for drinking purposes, in addition to finding the model based on past information to predict the quality of treated wastewater produced in each WTP using an artificial neural network (ANN) approach. The selected parameters for this study were turbidity, total hardness, total solids, suspended solids, and alkalinity. The results showed that all the WTPs possessed a high rate of efficiency in the removal of turbidity from raw water. Also, the results of the water quality index for all WTPs were classified over a study period of three years from 2015 to 2017 as being a good water quality and based on these results, the water treatment plants can be considered to be doing efficient water treatment process. The ANN model has been found at all WTPs to have a coefficient of determination (R2) for expected models was more than 0.7 to provide a WQI prediction tool that can be used with a moderate level of predictive acceptance to describe the suitability of WTP water quality for drinking purposes.
This study investigated a novel application of forward osmosis using different types of draw solutions for oilfield produced water treatment from the East Baghdad oilfield affiliated to the Midland Oil Company (Iraq). Magnesium chloride (MgCl2) and magnesium sulfate (MgSO4) were used as draw solutions in forward osmosis process to evaluate their effectiveness. Experiments were conducted in a laboratory scale forward osmosis system with cellulose triacetate hollow fiber membrane. In this work, sodium chloride solution was used as a feed solution with a concentration of 76 g/L (same concentration as the East Baghdad oilfield produced water) and the applied external pressure on the feed solution side was 2 bar. The impact of draw solution (DS)
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Abstract
This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model
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The inhibitive action of polyvinyl alcohol –sodium nitrite (PVASN) composite on the corrosion of mild steel in simulated cooling water (SCW) has been investigated by weight loss and potentiodynamic polarization. The effect of composite concentration (PVA/SN) , pH, and exposure time on corrosion rate of mild steel were verified using 2 levels factorial design and surface response analysis through weight loss approach, while the electrochemical measurements were used to study the behavior of mild steel in (SCW) with pH between 6 and 8 and in absence and presence of (PVA) in solution containing different concentration of NaNO2. It was verified that all three main variables studied were statistically significant while their interaction is
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This study is conducted to investigate the validity of using different levels of Rustumiya sewage water for irrigation and their effects on corn growth and some of the chemical properties of the soil such as electrical conductivity and soil pH in extract soil paste , the micro nutrient content in soil and plant which are ( Fe , Mn , Zn , Cu , Cd , Pb ). Three levels of sewage water ( 0 , 50 , 100 )% in two stages were used ,the three levels of wastewater ( without soil fertilization ) were used in the first stage , Where 80 Kg N /D+50Kg P2O5 /D was added to the soil as fertilizer in the control (0%) treatment and 40 Kg N/D+25Kg P2O5/D were added to 50 and 100% levels in the second stage .Corn seeds were planted in 12kg plastic pots in Com
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
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