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FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, with a
good degree of accuracy reaching 97.26, 95.92 and 86.43% respectively. These ANN models could be used as a support for workers in operating the filters in water treatment plants and to improve water treatment process. With the use of ANN, water systems will get more efficient, so reducing operation cost and improving the quality of the water produced.

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Publication Date
Tue Dec 16 2008
Journal Name
Journal Of Planner And Development
Evaluation of the efficiency of the regional transport network of the district center of Mahmudiya
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The Study aims at evaluating the efficiency of the regional transportation net in Al-mahmoodiya Qadaa center. The bus station of the Qadaa center is suffering from heavy traffic jam, which is due to the ongoing movement of the adjacent provinces, particularly the small cities. They vary in the degree of their link by the regional transportation net that links the province with the centers of big cities. That affects the traffic flow of the civilians of these cities and their daily activities in hierarchical way To achieve the purpose of the study, a questionnaire has been constructed to collect data through selecting a random sample including the passengers who are coming to the bus station in Al-Mahmoodiya center to know the flo

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Intelligent Systems And Applications In Engineering
Artificial Intelligence Based Statistical Process Control for Monitoring and Quality Control of Water Resources: A Complete Digital Solution
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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Effect of Laser Surface Modification on the Corrosion Resistance of Dental Alloys in Artificial Saliva Containing Alcoholic Beverages
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The objective of this study is to demonstrate the corrosion behavior of dental alloys Co-Cr-Mo, Ni-Cr-Mo and Ti-Al-V in artificial saliva at pH=4 and 37oC enriched with ethyl alcohol at 8% percentage. The linear and cyclic polarizations were investigated by electrochemical measurements. Laser surface modification was achieved for the three dental alloys to improve corrosion resistance. The results show that corrosion resistance of Co-Cr-Mo and Ni-Cr-Mo alloys only were increased after laser treatment due to the fact that laser radiation has caused a smoother surface, in addition to the decrement in corrosion current densities (icorr) for Co-Cr-Mo and Ni-Cr-Mo alloys and the reverse scan in cyclic polarization became in the wider range of

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Clinical And Experimental Dentistry
Resistance of bonded premolars to four artificial ageing models post enamel conditioning with a novel calcium-phosphate paste
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Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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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

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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Numerical modeling of performance of olive seeds as permeable reactive barrier for containment of copper from contaminated groundwater
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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Publication Date
Fri Mar 08 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Sorption is a key factor in removal of organic and inorganic contaminants from their aqueous solutions. In this study, we investigated the removal of Xylenol Orange tetrasodium salt (XOTS) from its aqueous solution by Bauxite (BXT) and cationic surfactant hexadecyltrimethyl ammonium bromide modified Bauxite (BXT-HDTMA) in batch experiments. The BXT and BXT-HDTMA were characterized using FTIR, and SEM techniques. Adsorption studies were performed at various parameters i.e. temperature, contact time, adsorbent weight, and pH. The modified BXT showed better maximum removal efficiency (98.6% at pH = 9.03) compared to natural Bauxite (75% at pH 2.27), suggesting that BXT-HDTMA is an excellent adsorbent for the removal of XOTS from water. The equ

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Publication Date
Sun Aug 31 2014
Journal Name
Arabian Journal Of Geosciences
Petroleum system modeling and risk assessments of Ad’daimah oil field: a case study from Mesan Governorate, south Iraq
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