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joe-2156
Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network
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The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , water concentration and temperature. The output is average corrosion rate .The performance of the two training algorithms, gradient descent with momentum and Levenberg-Marquardt, are compared to select the most suitable training algorithm for corrosion rate model. The model can be used to calculate the average corrosion rate properties of carbon steel alloy as functions of Reynolds number, water concentration and temperature. Accordingly, the combined influence of these effective parameters and the average corrosion rate is simulated. The results show that the corrosion rate increases with the increase of temperature, Reynolds number and the increase of water concentration.

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Publication Date
Sun Aug 24 2025
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of Acidity Level on Ions Released and Corrosion of Metal Orthodontic Appliances at Different Time Intervals (An In vitro Study)
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ABSTRACT Background: This study measured the effects of three parameters pH value, length of immersion and type of archwire on metal ions released from orthodontic appliances. Materials and Methods: Ninety maxillary halves simulated fixed orthodontic appliances that were immersed in artificial saliva of different pH values (6.75, 5 and 3.5) during 28 day period. Three types of archwires were used: stainless steel, nickel titanium and thermal activated nickel titanium. The quantity of nickel and chromium ions was determined with the use of atomic force spectrophotometer while iron ions by spectrophotometer. Each orthodontic set was weighted two times, before the ligation and immersion in the artificial saliva and after 28 days at the end of

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
tourism planning and its impact in reducing the unemployment rate in Iraq for the period (1985 – 2015) An analytical study
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Abstract

     The problem of the study is the main question (Can tourism planning address the phenomenon of unemployment in Iraq ?) , And the importance of the study in the fact that the tourism sector can become an effective development alternative in many countries, especially Iraq, as tourism contributes to diversify sources of income and stimulate other economic sectors , We know how important Iraq's qualifications are in the field of tourism and what it can generate on the public treasury, To confirm the current study on the need to pay attention to tourism planning for its role in providing employment opportunities that reduce the unemployment rate in the future.

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Formulation and Characterization of Nimodipine Nanoparticles for the Enhancement of solubility and dissolution rate
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Nimodipine (NMD) is a dihydropyridine calcium channel blocker useful for the prevention and treatment of delayed ischemic effects. It belongs to class ? drugs, which is characterized by low solubility and high permeability. This research aimed to prepare Nimodipine nanoparticles (NMD NPs) for the enhancement of solubility and dissolution rate. The formulation of nanoparticles was done by the solvent anti-solvent technique using either magnetic stirrer or bath sonicator for maintaining the motion of the antisolvent phase. Five different stabilizers were used to prepare NMD NPs( TPGS, Soluplus®, HPMC E5, PVP K90, and poloxamer 407). The selected formula F2, in which  Soluplus 

has been utilized as a stabilizer, has a par

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Phytochemical Study of some Flavonoids Present in the Fruits of Two Ammi L. Species Wildly Grown in Iraq
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Ammi species belong to the family Umbellifereae that provide a host of bioactive compounds (mainly coumarins and flavonoids) of important biological activities, like prevention and treatment of heart and vascular disease and some types of cancer. Literature survey revealed that there was no study concerning Ammi flavonoids in Iraq. Ammi majus and Ammi visnaga, which are wildly grown in Iraq, were chosen for this study. This study concerned with extraction, identification, isolation, and purification of some biologically important flavonols quercetin and kaempferol from the fruits of Ammi majus and Ammi visnaga. Extraction of these flavonols was carried out using 85% methanol and 90% e

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Biodegradation of Anthracene Compound by Two Species of Filamentous Fungi
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Isolation and identification fungi of Emericella nidulans and Aspergillus flavus from a pinkish and yellowish artificial clay, by using potato dextrose agar (PDA). Results revealed that E. nidulans was the best for degrading anthracene (92.3%) with maximum biomass production (3.7gm/l), compared to A. flavus with the rate of degradation (89%) and biomass production of (1.2gm/l), when methylene blue was used as redox indicator after incubating in a shaker incubator 120rpm at 30Co for 8days. Results indicated that E. nidulans has a high ability of anthracene degradation with the rate of (84%), while A. flavus showed the lower level with (77%) by using HPLC.

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Sat Jul 27 2024
Journal Name
Scientific Journal Of Sport And Performance
effect of a laser device on some biomechanical variables of the rotational phase in the achievement of 100 m freestyle swimming for the Iraqi team (16-18 years old)
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The researchers have discovered weaknesses in the rotational phase of the 100-meter freestyle event, including a lack of proper movement direction and control of biomechanical variables necessary for swimmers to achieve high rotational accuracy, which leads to outperforming competitors. The objective of this study was to investigate the effect of using a laser device on improving the performance of the rotational phase among swimmers on the Iraqi national team. The experimental approach was conducted on a sample of 6 swimmers, representing 100% of the target population. The researchers concluded that the utilization of a proposed laser device in the rotational phase resulted in positive differences in biomechanical variables, contri

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Publication Date
Tue Jan 01 2013
Journal Name
Communications And Network
Link and Cost Optimization of FTTH Network Implementation through GPON Technology
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