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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
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Evaluating Educational Programs in Combating Indecent Behaviors Among University Students Using Structural Equation Modeling (Field study: Northern Border University)
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The study aimed to evaluate educational programs efficiency in applying the best educational practices to educate students from the dangers of indecent behaviors, in line with higher education policy and the appropriateness of educational program dimensions to spread awareness among students to not fall into the indecent behaviors clutches. The study adopted the inductive exploratory approach through structural equation modeling and the descriptive analysis of the collected data from randomly selected sample (n=385) from educational academics at Northern Border University in the Saudi Arabia using a specially designed survey tool to meet study purposes to evaluate dimensions of teaching methods, evaluation tools, training courses, course

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Publication Date
Mon May 31 2021
Journal Name
Journal Of Research In Medical And Dental Science
A Stereomicroscopic Evaluation of Four Endodontic Sealers Penetration into Artificial Lateral Canals Using Gutta-Percha Single Cone Obturation Technique
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A Stereomicroscopic Evaluation of Four Endodontic Sealers Penetration into Artificial Lateral Canals Using Gutta-Percha Single Cone Obturation Technique, Omar Jihad Banawi*, Raghad

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Use Dynamic Bayesian network to estimate the reliability of Adamia Water Network
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Abstract\

In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the

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Publication Date
Fri Aug 30 2019
Journal Name
Environmental Engineering Research
Numerical modeling of two-dimensional simulation of groundwater protection from lead using different sorbents in permeable barriers
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This study is to investigate the possibility of using activated carbon prepared from Iraqi date-pits (ADP) which are produced from palm trees (Phoenix dactylifera L.) as low-cost reactive material in the permeable reactive barrier (PRB) for treating lead (Pb<sup>+2</sup>) from the contaminated groundwater, and then compare the results experimentally with other common reactive materials such as commercial activated carbon (CAC), zeolite pellets (ZP). Factors influencing sorption such as contact time, initial pH of the solution, sorbent dosage, agitation speed, and initial lead concentration has been studied. Two isotherm models were used for the description of sorption data (Langmuir and Freundlich). The maximum lead sorp

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Optimization and Modeling the Performance of a Mediator-less Microbial Fuel Cell using Butler-Volmer-Monod Model
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In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m3

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Publication Date
Tue Sep 07 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Wellbore instability management using geomechanical modeling and wellbore stability analysis for Zubair shale formation in Southern Iraq
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Abstract<p>Wellbore instability problems cause nonproductive time, especially during drilling operations in the shale formations. These problems include stuck pipe, caving, lost circulation, and the tight hole, requiring more time to treat and therefore additional costs. The extensive hole collapse problem is considered one of the main challenges experienced when drilling in the Zubair shale formation. In turn, it is caused by nonproductive time and increasing well drilling expenditure. In this study, geomechanical modeling was used to determine a suitable mud weight window to overpass these problems and improve drilling performance for well development. Three failure criteria, including Mohr–Coulomb, modifie</p> ... Show More
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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Neural Tube Defects in Iraq
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1.
Embryonic Origin of Neural Tube Defects.
Insaf Jasim Mahmoud
2.
Etiology of Neural Tube Defectss.
Ali Abdul Razzak Obed
3.
Epidemiology of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi
4.
Surgical Management of Neural Tube Defects.
Laith Thamer Al-Ameri
5.
Prevention of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi

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Publication Date
Sat Jan 01 2022
Journal Name
Encyclopedia Of Smart Materials
Modeling Behavior of Magnetorheological Fluids
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Publication Date
Sun Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Improving the Network Lifetime in Wireless Sensor Network for Internet of Thing Applications
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Mobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kern

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Use Of Artificial Neural Networks In Developing The Role Of Auditor In Discovering Fundamental Errors: An Applied Research In General Company for Electrical Industries and Nasr General Company for Mechanical Industries
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Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

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