Solid‐waste management, particularly of aluminum (Al), is a challenge that is being confronted around the world. Therefore, it is valuable to explore methods that can minimize the exploitation of natural assets, such as recycling. In this study, using hazardous Al waste as the main electrodes in the electrocoagulation (EC) process for dye removal from wastewater was discussed. The EC process is considered to be one of the most efficient, promising, and cost‐effective ways of handling various toxic effluents. The effect of current density (10, 20, and 30 mA/cm2), electrolyte concentration (1 and 2 g/L), and initial concentration of Brilliant Blue dye (15 and 30 mg/L) on the efficiency of the EC process were examined in this study. The results show that removal efficiency increased with current density and sodium chloride (NaCl) concentration and decreased with initial dye concentration. The electrical power and electrodes consumed increased with an increase in current density and decreased notably with increased NaCl. The optimum current density and amount of NaCl were 20 mA/cm2 and 2 g/L, respectively to attain highest values of E133 brilliant blue dye removal. The EC process was examined using adsorption isotherms and kinetics models. Those results showed that the Langmuir isotherm matched the experimental data. Furthermore, the experimental data were followed the Elovich model kinetics.
Quantum dots of CdSe, CdS and ZnS QDs were prepared by chemical reaction and used to fabricate organic quantum dot hybrid junction device. QD-LEDs were fabricated using layers of ITO/TPD: PMMA/CdSe/Alq3, ITO/TPD: PMMA/CdS/Alq3 and ITO/TPD: PMMA/ZnS/Alq3 devices which prepared by phase segregation method. The hybrid white light emitting devices consists, of three-layers deposited successively on the ITO glass substrate; the first layer was of N, N’-bis (3-methylphenyl)-N, N’-bis (phenyl) benzidine (TPD) polymer mixed with polymethyl methacrylate (PMMA) polymers. The second layer was QDs while the third layer was tris (8-hydroxyquinoline) aluminium (Alq3
... Show More 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
... Show MoreThis study focused on a fundamental issue which was represented by ability of Iraqi central bank in facing the difficulty of determining the optimal ratio of liquidity in the Iraqi banks in terms of the balancing between its obligations to the depositors and borrowers, and liquidate their funds on one hand and the risks on the other hand.the search aimed for achieving the goals which represented by identifying the possibility of Iraqi banks to apply the regulations rules and instructions issued by central bank of Iraq in determining ratio of liquidity and its appropriate with Iraqi banks action to implement a reasonable profit to&
... Show Morethis study was perform to defined the effect of fungus Metarhiziumanisopliae Sorokin with concentrations 5x101, 5x103 and 5x105 spore/ ml and Actelic insecticide with concentration 0.001% in in rate of germinate treated string bean seeds also study effect of packed bags in two different type: jute and polypropylene bags which treated with fungal suspension pervious mention and insecticide in rate infested the string bean seeds packed in it.Results of the study showed the following: Lower rate of weight loss of cowpea seeds appear in poly propylene bags 4.41, 5.95% after six months of treatment with 5x 105 spore/ ml and Actelic insecticide respectively compared with 15.08% to control treatment. The fungal concentrations and insecticide not
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This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per
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