Electrocoagulation is an electrochemical method for treatment of different types of wastewater whereby sacrificial anodes corrode to release active coagulant (usually aluminium or iron cations) into solution, while simultaneous evolution of hydrogen at the cathode allows for pollutant removal by flotation or settling. The Taguchi method was applied as an experimental design and to determine the best conditions for chromium (VI) removal from wastewater. Various parameters in a batch stirred tank by iron metal electrodes: pH, initial chromium concentration, current density, distance between electrodes and KCl concentration were investigated, and the results have been analyzed using signal-to-noise (S/N) ratio. It was found that the removal efficiency of chromium increased with increasing current density and KCl concentration, and decreases with increasing initial chromium concentration and distance between electrodes, while pH shows peak performance curve. Experimental work have been performed for synthetic solutions and real industrial effluent. The results showed that the removal efficiency of synthetic solution is higher than industrial wastewater, the maximum removal for prepared solution is 91.72 %, while it was 73.54 % for industrial wastewater for the same conditions.
Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl
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The present work reports on the performance of three types of nanofiltration membranes in the removal of highly polluting and toxic lead (Pb2+) and cadmium (Cd2+) from single and binary salt aqueous solutions simulating real wastewaters. The effect of the operating variables (pH (5.5-6.5), types of NF membrane and initial ions concentration (10-250 ppm)) on the separation process and water flux was investigated. It was observed that the rejection efficiency increased with increasing pH of solution and decreasing the initial metal ions concentrations. While the flux decreased with increasing pH of solution and increasing initial metal ions concentrations. The maximum rejection of lead and cadmium ion
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert
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This research aims to estimate stock returns, according to the Rough Set Theory approach, test its effectiveness and accuracy in predicting stock returns and their potential in the field of financial markets, and rationalize investor decisions. The research sample is totaling (10) companies traded at Iraq Stock Exchange. The results showed a remarkable Rough Set Theory application in data reduction, contributing to the rationalization of investment decisions. The most prominent conclusions are the capability of rough set theory in dealing with financial data and applying it for forecasting stock returns.The research provides those interested in investing stocks in financial
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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