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Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Tue Mar 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Effluent Quality Assessment Monitoring of Al-Rustamiya Sewage Treatment Plant Using Geographical Information System (GIS)
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Abstract<p>Water quality assessment offers a scientific basis for water resource development and management. This research aims to assessment of Al-Rustamiya sewage treatment plant depending on annually changes and produces maps that declare changes on parameter during a period (2015-2018). Based on prior Government Department Baghdad Environment data which annually feature changes for samples from Northern Rustamiya have been estimated as a working model. Drawn a map of the Diyala River shows annual changes in the characteristics of the Diyala River, based on northern and southern Rustamiya effluent samples, and Diyala River samples. The characteristics that research focused on were biochemical</p> ... Show More
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
Extraction of Bovine Serum Albumin by Aqueous Two-Phase System Using PEG4000/Sodium Citrate and PEG8000/Sodium Phosphate
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Aqueous Two Phase System (ATPS) or liquid-liquid extraction is used in biotechnology to recover valuable compounds from raw sources. In Aqueous Two-Phase Systems, many factors influence the Partition coefficient, K, (which is the ratio of protein concentration in the top phase to that in the bottom phase) and the Recovery percentage (Rec%). In this research, two systems of ATPS were used: first, polyethylene glycol (PEG) 4000/Sodium citrate (SC), and the second, PEG8000/ Sodium phosphate (SPH), for the extraction of Bovine Serum Albumin (BSA). The behavior of Rec% and K of pure (BSA) in ATPS has been investigated throughout the study by the effects of five parameters: temperature, concentration of polyethylene glycol (P

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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Assessment of Delayed/Slow-Release Diclofenac Sodium Edible Organogel Utilizing Low Molecular Weight Organogelators
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Organogel as a system was to estimate its capacity to delay and slow the drug release in the duodenum. The gelators, 12HSA (12-hydroxystearic acid), span 60. span 40 were used; the castor oil (CO) and anise oil (AO) also represented the liquid phase. To achieve the goal of this work was by using diclofenac sodium (DS). Organogels specifications were by estimating thermal attitude using tabletop rheology and differential scanning calorimetry (DSC). The organogel strength study was by applying oscillatory rheology tests the amplitude sweep and the frequency sweep. Realizing the morphology of the organogel was done utilizing an optical microscope. CO and AO binding capacity was also manifested. The transition temperatures for all organogels

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Publication Date
Fri Dec 20 2024
Journal Name
Bulletin Of The Iraq Natural History Museum
FIRST RECORD OF THE NORTH AFRICAN CATFISH CLARIAS GARIEPINUS (BURCHELL, 1822) (SILURIFORMES, CLARIIDAE) IN TIGRIS RIVER, IRAQ
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The current study aimed to determine the morphometric and meristic characteristics of the North African catfish Clarias gariepinus (Burchell, 1822). Six specimens of C. gariepinus were collected from the Tigris River, in central Iraq. This study is considered the confirmation first record of this species in Iraq, and the second documentation of this exotic fish. The present species is characterized by a very long dorsal fin, a rounded caudal fin and four pairs of barbels.

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned

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Publication Date
Thu Jan 01 2015
Journal Name
Egyptian Journal Of Aquatic Research
Ecological factors affecting the distribution of the zooplankton community in the Tigris River at Baghdad region, Iraq
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Publication Date
Mon Feb 01 2021
Journal Name
Https://www.researchgate.net/journal/university-of-baghdad-engineering-journal-1726-4073
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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