Background: Large amounts of oily wastewater and its derivatives are discharged annually from several industries to the environment. Objective: The present study aims to investigate the ability to remove oil content and turbidity from real oily wastewater discharged from the wet oil's unit (West Qurna 1-Crude Oil Location/ Basra-Iraq) by using an innovated electrocoagulation reactor containing concentric aluminum tubes in a monopolar mode. Methods: The influences of the operational variables (current density (1.77-7.07 mA/cm2) and electrolysis time (10-40 min)) were studied using response surface methodology (RSM) and Minitab-17 statistical program. The agitation speed was taken as 200 rpm. Energy and electrodes consumption had been studi

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

New complexes were synthesized with Schiff base tetradentate ligand (L). The ligand was synthesized by the condensation reaction of the dimedone with 2-hydroxybenzohydrazide. The formula of complexes [M(L) (H2O)2].Cl2, where M represents Mn(II), Ni(II) Cu(II), [Co(L)Cl.H2O]Cl and [Zn(L)(H2O)2]Cl2.2H2O. The ligand was identified using m.p., UV-Vis, FT-IR, Mass, 1H-NMR, and C.H.N. These complexes were characterized using techniques including infrared, UV-Vis absorption, magnetic susceptibility, molar conductivity, elemental analyses, thermogravimetric analysis (TGA), chloride content determination using Mohr’s method, and atomic absorption spectroscopy. The measurements revealed that the complexes are electrolytic. FT-IR results dem

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe