Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The prediction models of the turbidity removal are presented. Results found that the estimating of the turbidity removal efficiency by ANN and MLR model could be successful. Moreover, results showed that influent and effluent turbidity concentration have more effect on removal efficiency predicting from the other parameters. Finally, the ANN model could be more accurate than the MLR model according to the coefficient of correlation (0.925).
This paper was aimed to study the efficiency of forward osmosis (FO) process as a new application for the treatment of wastewater from textile effluent and the factors affecting the performance of forward osmosis process.
The draw solutions used were magnesium chloride (MgCl2), and aluminum sulphate (Al2 ( SO4)3 .18 H2O), and the feed solutions used were reactive red, and disperse blue dyes.
Experimental work were includes operating the forward osmosis process using thin film composite (TFC) membrane as flat sheet for different draw solutions and feed solutions. The operating parameters studied were : draw solutions concentration (10 – 90 g/l), feed solutions concentration (5 – 30 mg/l), draw solutions flow rate (10 – 50 l/hr
Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
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In this manuscript, a simple new method for the green synthesis of platinum nanoparticles (Pt NPs) utilizing F. carica Fig extract as reducing agent for antimicrobial activities was reported. Simultaneously, the microstructural and morphological features of the synthesized Pt NPs were thoroughly investigated. In particular, the attained Pt NPs exhibited spherical shape with diameter range of 5-30 nm and root mean square of 9.48 nm using Transmission Electron Microscopy (TEM) and Atomic Force Microscopy (AFM), respectively. Additionally, the final product (Pt NPs) was screened as antifungal and antibacterial agent against Candida and Aspergillus species as well as Gram-positive Staphyllococcus aureus and G
... Show MoreHard-grade asphalt binders, such as AC 20–30, offer excellent resistance to permanent deformation but are inherently brittle, making them highly susceptible to fatigue and low-temperature cracking. While polymer modification addresses these issues, virgin polymers remain expensive. Despite the growing interest in recycled plastics, the rheological impact of complex waste streams, specifically polyvinyl chloride (PVC) derived from flex banners containing plasticizers, on excessively stiff binders within the complete Superpave Performance Grading (PG) framework remains critically underexplored. This study introduces a novel valorization approach by utilizing solvent-extracted flex banner waste (WPVC) as a dual-action modifier. It leverages
... Show MoreA poetic vision appeared in the poem of Al-Abbas bin Mardas Al-Sulami. He lived in the eras of pre-Islamic times and the emergence of Islam. The focus of this research: is the study of poetic text in the pre-Islamic era and the era of early Islam. The research followed a method in treating poetic texts, as it is based on presenting poetic texts from the collection of Al-Abbas bin Mardas, explaining the features of his poetic vision, and examining all the external factors that surrounded the poet and influenced his vision and all his thoughts. The results of this research was that Al-Abbas Ibn Mardas revealed some of the positions that he found contradicted the authentic Arab value before the advent of Islam, and the poet Abbas bin Mardas tr
... Show MoreThe present study is an attempt to throw light on the nature of the US policy regarding the Middle East region as portrayed by AI-Sabah, Al-Mashriq and Tariq Al-Shaab papers over a period of three months from 1st of July to 30th of September 2013.
In writing this study, a number of goals have been set by the researcher. These goals may include but in no way limited to the nature of the US image as carried by the above three papers, the nature of the topics tackled by them and the nature of the Arab countries which received more and extensive coverage than others.
A qualitative research approach is proposed for the study. This approach has allowed the researcher to arrive at definite answers for the possible questions rais
... Show MoreIn this research, radon concentrations in some types of healthy drinking water samples available in Iraq's market were measured using a technique called Durridge RAD-7-H2O with closed loop. Then the rate of annual effective dose in human taken this water is determined.
It was found that, radon concentrations in studied samples ranged between 1.2 Bq.m-3 to 142 Bq.m-3. The results of the radon concentrations and the rate of annual effective dose for drinking water samples were significantly lower than the USEPA and WHO recommended limits that equal 500 Bq/m3 and 1 mSv/y resp
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