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Prediction of solubility of vitamins in the mixed solvents using equation of state
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Publication Date
Mon Jan 01 2018
Journal Name
Rehabend
Prediction of impact force-time history in sandy soils
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Publication Date
Sun Mar 01 2009
Journal Name
The Third International Conference Of The College Of Science –university Of Baghdad
On Maximal solution of nonlinear operator equation
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
EX-SITU Characterization of Luffa aegyptaica in Lagos State, Nigeria
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Luffa aegyptiaca is a plant of multi-purpose importance whose usefulness cuts across virtually all areas of life. This study has characterized L. aegyptiaca in Lagos state and determined the mineral, proximate, phytochemical as well as the heavy metal accumulation potential. Samples were collected from the 20 Local Government Areas (LGAs) in Lagos state at 2 samples per location.   Genetic similarity and intra-specific variation in 40 samples of L. aegyptiaca were determined using 3 Random Amplified Polymorphic DNA (RAPD) primers which yielded a total of 42 markers of which 25 was polymorphic. The maximum number of bands (14) was produced by OPC4 while the minimum (7) were produced by OPAF20. Percenta

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Estimation Mean Wind Speed in Iraq By Using Parametric And Nonparametric Linear Mixed Models
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In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and   then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g

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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
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region
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Scopus (12)
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Publication Date
Sat Oct 06 2012
Journal Name
Journal Of Engineering
Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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