The combined system of electrocoagulation (EC) and electro-oxidation (EO) is one of the most promising methods in dye removal. In this work, a solution of 200 mg/l of Congo red was used to examine the removal of anionic dye using an EC-EO system with three stainless steel electrodes as the auxiliary electrodes and an aluminum electrode as anode for the EC process, Cu-Mn-Ni Nanocomposite as anode for the EO process. This composite oxide was simultaneously synthesized by anodic and cathodic deposition of Cu (NO3)2, MnCl2, and Ni (NO3)2 salts with 0.075 M as concentrations of each salt with a fixed molar ratio (1:1:1) at a constant current density of 25 mA/cm2. The characteristics structure and surface morphology of the deposited nano oxides onto the graphite substrates were determined by (XRD), (FE-SEM), (AFM), and (EDX). The results shown that nano Cu-Mn-Ni oxides were successfully deposited onto the anode and cathode. The crystal size and root mean square for the cathode were 30.79 nm and 79.36 nm, respectively, while for the anode, they were 24.19 nm and 41.88 nm, respectively. Furthermore, the combined system was examined for C.D, NaCl concentration, and time. In the EC-EO combined system, the cathode and anode were efficient when used as anodes for the EO process, besides aluminum. The cathode was more effective in the removal process than the anode due to its larger crystal size and the rough, granular shape of its surface. When current density (C.D) increased from 3 to 6 mA/cm², the removal efficiency shifted from 95% to 98%. However, excellent removal of 98% and 96.5% was attained with 1.665 and 2.0859 kWh/kg of dye as energy consumption in the presence and absence of NaCl salt, respectively by applying 6 mA/cm2 within 20 min of electrolysis.
The research aimed to shed light on the impact of international Accounting Standard No (21) on tax obstacles represented by (tax evasion, double taxation) The financial statements of a group of banks operating in the private sector were relied upon to know the impact of the standard on tax obstacles, as well as knowing the amount of amounts, The researcher relied on the method of financial analysis of that data, which was obtained from the website of the Securities Commission, and conducted personal interviews with a number of university professors, chartered accountants, financial experts, banks, and the General Authority for Taxes to benefit from their
... Show MoreAPDBN Rashid, Review of International Geographical Education Online (RIGEO), 2021
The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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