Industrial wastewater containing nickel, lead, and copper can be produced by many industries. The reverse osmosis (RO) membrane technologies are very efficient for the treatment of industrial wastewater containing nickel, lead, and copper ions to reduce water consumption and preserving the environment. Synthetic industrial wastewater samples containing Ni(II), Pb(II), and Cu(II) ions at various concentrations (50 to 200 ppm), pressures (1 to 4 bar), temperatures (10 to 40 oC), pH (2 to 5.5), and flow rates (10 to 40 L/hr), were prepared and subjected to treatment by RO system in the laboratory. The results showed that high removal efficiency of the heavy metals could be achieved by RO process (98.5%, 97.5% and 96% for Ni(II), Pb(II) and Cu(II) ions respectively). The permeate flux for all H.M ions was ranged between (10 to 56 L/m2.hr). The low level of the heavy metals concentration in the permeate implies that water with good quality could be reclaimed for further reuse. The RO membrane is characterized by very high efficiency as the H.M. ions removal of up to (97%) with good productivity and medium pressure that means a medium cost of the RO system.
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
... Show MoreThe current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo
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
... Show MoreIn this study, Yogurt was dried and milled, then shaked with distilled water to remove the soluble materials, then again dried and milled. Batch experiments were carried out to remove hexavalent chromium from aqueous solutions. Different parameters were optimized such as amount of adsorbent, treatment time, pH and concentration of adsorbate. The concentrations of Cr6+ in solutions are determined by UV-Visible spectrophotometer. Maximum percentage removal of Cr6+ was 82% at pH 2. Two equilibrium adsorption isotherms mechanisms are tested Langmuir and Freundlich, the results showed that the isotherm obeyed to Freundlich isotherm. Kinetic models were applied to the adsorption of Cr6+ ions on the adsorbents, ps
... Show MoreIn this study, the concentrations of uranium for four species of plants; Spinacia, Brassica Oleracea, BEASSICA Oleracea Var Capitata and Beta Vulgaris were measured in addition to the measurement of uranium concentrations in the selected soil by calculating the number of significant traces of alpha in CR-39. The 2.455 Bq/kg in Spinacia plant were the highest concentration while the lowest concentration of uranium were 1.91 Bq/kg in BEASSICA Oleracea Var Capitata plant. As for the transfer factor, the highest value 0.416 were found in Spinacia plant and the lowest value 0.323 were found in BEASSICA Oleracea Var Capitata plant. The uranium in the models studied in it did not exceed the international limit, according to the International Atomi
... Show MoreThe adsorption of Pb(II) ions onto bentonite and activated carbon was investigated. The effects of pH, initial adsorbent dosage, contact time and temperature were studied in batch experiments. The maximum adsorption capacities for bentonite and activated carbon were 0.0364 and 0.015 mg/mg, respectively. Thermodynamic parameters such as Gibbs free energy change, Enthalpy change and Entropy change have been calculated. These thermodynamic parameters indicated that the adsorption process was thermodynamically spontaneous under natural conditions and the adsorption was endothermic in nature. Experimental data were also tested in terms of adsorption kinetics, the results showed that the adsorption processes followed well pseudo second- order
... Show MoreIn this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.
In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
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