This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

. New Schiff base ligand 2-((4-amino-5-(3, 4, 5-trimethoxybenzyl) pyrimidin2-ylimino) (phenyl)methyl)benzoic acid] = [HL] was synthesized using microwave irradiation trimethoprim and 2-benzoyl benzoic acid. Mixed ligand complexes of Mn((ІІ), Co(ІІ), Ni(ІІ), Cu(ІІ), Zn(ІІ) and Cd(ІІ) are reacted in ethanol with Schiff base ligand [HL] and 8-hydroxyquinoline [HQ] then reacted with metal salts in ethanol as a solvent in (1:1:1) ratio. The ligand [HL] is characterized by FTIR, UV-Vis, melting point, elemental microanalysis (C.H.N), 1H-NMR, 13C-NMR, and mass spectra. The mixed ligand complexes are characterized by infrared spectra, electronic spectra, (C.H.N), melting point, atomic absorption, molar conductance and magnetic m

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

Removal of heavy metals from waste water has received a great deal of attention. The compare Cr
(VI) adsorption characteristics removing from wastewater by using thermally modified and non-modified
eggshells were examined

Titanium oxide nanoparticles-modified smectite (SMC-nTiO2) as a low-cost adsorbent was investigated for the removal of Rhodamine B (RhB) from aqueous solutions. The adsorbents (SMC and SMC-nTiO2) were characterized by scanning electron microscopy, Fourier transforms infrared spectroscopy, and energy-dispersive X-ray spectroscopy. The effects of various parameters like contact time, adsorbent weight, pH, and temperatures were examined. Three kinetic equations (pseudo-first-order (PFO), pseudo-second-order (PSO), and intra-particle diffusion) were used to evaluate the experimental kinetic of the data and the results showed that the adsorption process is in line with the PSO kinetic model. Adsorption equilibrium isotherms were modeled using La

Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica

Lead remediation was achieved using simple cost, effective and eco-friendly way from industrial wastewater. Phragmitesaustralis (P.a) (Iraqi plant), was used as anovel biomaterial to remove lead ions from synthesized waste water. Different parameters which affected on adsorption processes were investigated like adsorbent dose, pH, contact time, and adsorbent particle size, to reach the optimized conditions (maximum adsorption). The adsorption of Pb (?) on (P.a) involved fast and slow process as a mechanism steps according to obey two theoretical adsorption isotherms; Langmuir and Freundlich. The thermos dynamic adsorption parameters were evaluated also. The (?H) obtained positive value that meanes adsorption of lead ions was an endothermic

Lead remediation was achieved using simple cost, effective and eco-friendly way from industrial wastewater. Phragmitesaustralis (P.a) (Iraqi plant), was used as anovel biomaterial to remove lead ions from synthesized waste water. Different parameters which affected on adsorption processes were investigated like adsorbent dose, pH, contact time, and adsorbent particle size, to reach the optimized conditions (maximum adsorption). The adsorption of Pb (?) on (P.a) involved fast and slow process as a mechanism steps according to obey two theoretical adsorption isotherms; Langmuir and Freundlich. The thermos dynamic adsorption parameters were evaluated also. The (?H) obtained positive value that meanes adsorption of lead ions was an endothermic

The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w