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Modeling BOD of the Effluent from Abu-Ghraib Diary Factory using Artificial Neural Network October 2018
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The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed ANN model to predict BOD of the effluent gave a high degree of correlation reaching 93.5% with seven input parameters. This model can be queried to determine the best combination of operating conditions needed in the wastewater treatment plant to achieve the desired effluent disposal limits.

Publication Date
Fri Jan 01 2021
Journal Name
Lecture Notes In Networks And Systems
Evaluating the Efficiency of Regional Transport Network
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Psychological pressures and their relationshiptothe competitive orientation of football playersinthe Iraqi Premier League for the 2018-2019season
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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Data And Network Science
The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

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Publication Date
Mon May 09 2022
Journal Name
International Academic Journal Of Economics
Analysis of the Relationship between Fiscal Policy Shocks and Monetary Stability in Iraq's Economy for the Period 1990-2018
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The research aims to measure the impact of positive and negative fiscal policy shocks on monetary stability in Iraq, which represents monetary stability as an indicator of real and price stability. Fiscal policy shocks are quantitative changes in public spending and public revenue affecting the output and price cycle, and fiscal policy despite the accompanying time gaps, but it remains a policy Influential and has a significant degree of impact on economic growth and development in developing countries. The fiscal policy represents a numerical translation of the economic and social objectives planned in the state's general budget tool consistent with the GDP cycle. The economic and social goals stem from the core of the functions and the ma

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The impact of financial development on economic growth in Iraq for the period (2004-2018):An Analytical Econometric Study
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            The objective of this study is to measure the impact of financial development on economic growth in Iraq over the period (2004-2018) by applying a fully corrected square model (FMOLS) Whereas, a set of variables represented by (credit-to-private ratio of GDP, the ratio of money supply in the broad sense of GDP, percentage of bank deposits from GDP) were chosen as indicators for measuring financial development and GDP to measure economic growth.

Major tests have been carried out, such as the stability test (Unite Root Test), the integration test (Cointegration). Results of the study showed that there

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Study the Effect of 12-Hydroxyoctadecanoic Acid Concentration on Preparation and Characterization of Floating Organogels using Cinnarizin as Modeling Drug
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This work targeted studying organogel as a potential floating system. Organgel has an excellent viscoelastic properties, floating system posses a depot property.  Different formulations of 12-hydroxyoctadecanoic acid (HOA) in sesame oil were gelled and selecting F1, F3 and F5 HOA organogels for various examinations: tabletop rheology, optical microscopy, and oscillatory rheology studies. Also, the floating properties studies were conducted at in vitro and in-vivo levels. Lastly, the in-vitro release study using cinnarizine (CN) was to investigate the organogel depot property. Based on the results, the selected concentrations of HOA in sesame oil organogels showed temperature transitions fr

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Publication Date
Fri Sep 25 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Occupational dental wear among El-Kubasis cement factory workers - An observational study
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Background: Loss of tooth structure may be due to tooth to tooth contact and presence of abrasive components in the work environment. The aim of study was planned to evaluate the occurrence of dental attrition among Cement factory workers. Material and Method: The Sample included all workers chronically exposed to cement dust in the EL-Kubaisa cement factory (95 workers). A comparative group of workers (97) were non-exposed to cement dust was selected. All workers were males in gender with age range (25-55) years. The assessment of tooth wear was based on the criteria of smith and knight, 1984. Results: The maximum tooth wear score for exposed workers was 84.2% while non exposed workers was 38.1%,with statistical differences between two g

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Publication Date
Thu May 25 2023
Journal Name
Polycyclic Aromatic Compounds
Effect of Modified Nano-Graphene Oxide and Silicon Carbide Nanoparticles on the Mechanical Properties and Durability of Artificial Stone Composites from Waste
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Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydropho

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