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Prediction of bearing capacity, angle of internal friction, cohesion, and plasticity index using ANN (case study of Baghdad, Iraq)
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and the plasticity index of the soil.

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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Study of using Mesocyclops hyalinus and Cyclops agilis as A biological Control of Anophles larvae
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The fresh water ecosystem constitute an essential and very important for human life, for this reason it should be kept away from all the chemical pollutants including the pesticides The best way for Fighting harmful insects.(such as Anophles larvae) is by the biological control.

 

In the present study two species of Cyclopoida: Copepod, Mesocyclops hyalinus and Cyclops agilis Ø¢ were used as predators for Anophles larvae.

 

The data showed that the percentages of predation were 65% and 56%

forM. hyalinus and C. agilis respectively

 

and the means of predation were 1.3 larvae/ female and 1.1

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Publication Date
Tue Sep 01 2020
Journal Name
Iraqi Journal Of Physics
Study of the nuclear structure of halo nuclei 23O and 24F using the two-body model
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The nuclear structure included the matter, proton and neutron densities of the ground state, the nuclear root-mean-square (rms) radii and elastic form factors of one neutron 23O and 24F halo nuclei have been studied by the two body model of  within the harmonic oscillator (HO) and Woods-Saxon (WS) radial wave functions. The calculated results show that the two body model within the HO and WS radial wave functions succeed in reproducing neutron halo in these exotic nuclei. Moreover, the Glauber model at high energy has been used to calculated the rms radii and reaction cross section of these nuclei.

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Publication Date
Mon Mar 01 2021
Journal Name
Iraqi Journal Of Physics
Study of the proton halo structure of nuclei 23Al and 27P using the binary cluster model
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The neutron, proton, and matter densities of the ground state of the proton-rich 23Al and 27P exotic nuclei were analyzed using the binary cluster model (BCM). Two density parameterizations were used in BCM calculations namely; Gaussian (GS) and harmonic oscillator (HO) parameterizations. According to the calculated results, it found that the BCM gives a good description of the nuclear structure for above proton-rich exotic nuclei. The elastic form factors of the unstable 23Al and 27P exotic nuclei and those of their stable isotopes 27Al and 31P are studied by the plane-wave Born approximation. The main difference between the elastic form factors of unstable nuclei and the

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Study the Quality of Nasopharyngeal plans Using Evaluation Indexes of IMRT and VMAT Treatment planning Techniques
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Radiation treatment has long been the conventional approach for treating nasopharyngeal cancer (NPC) tumors due to its anatomic features, biological characteristics, and radiosensitivity. The most common treatment for nasopharyngeal carcinoma is radiotherapy. This study aimed to assess the better quality of radiotherapy treatment techniques using intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT). The VMAT and IMRT are comparative techniques. Forty patients with nasopharyngeal carcinoma and forwarded for radiotherapy were treated with both advanced techniques, IMRT and VMAT, using eclipse software from Varian. The x-ray energy was set at 6 MV. The total prescribed dose was 70 Gy. The results show that the

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Publication Date
Tue Nov 01 2022
Journal Name
Chemical Methodologies
Study of Optical and Structural Properties of CdTe Quantum Dots Capped with 3MPA Using Hydrothermal Method
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Quantum dots (QDs) can be defined as nanoparticles (NPs) in which the movement of charge carriers is restricted in all directions. CdTe QDs are one of the most important semiconducting crystals among other various types where it has a direct energy gap of about 1.53 eV. The aim of this study is to exaine the optical and structural properties of the 3MPA capped CdTe QDs. The preparation method was based on the work of Ncapayi et al. for preparing 3MPA CdTe QDs, and hen, the same way was treated as by Ahmed et al. via hydrothermal method by using an autoclave at the same temperature but at a different reaction time. The direct optical energy gap of CdTe QDs is between 2.29 eV and 2.50 eV. The FTIR results confirmed the covalent bonding betwee

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Publication Date
Fri Jan 01 2021
Journal Name
Egyptian Journal Of Radiology And Nuclear Medicine
Spectrum of CT appearance and CT severity index of COVID-19 pulmonary infection in correlation with age, sex, and PCR test: an Iraqi experience
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Abstract<sec> <title>Background

Since June 2020, an explosion in number of new COVID-19 patients has been reported in Iraq with a steady increment in new daily reported cases over the next 3 months. The limited number of PCR kits in the country and the increment in the number of new COVID-19 cases makes the role of CT scan examinations rising and becoming essential in aiding the health institutions in diagnosing and isolating infected patients and those in close contacts. This study will review the spectrum of CT pulmonary changes due to COVID-19 infection and estimate the CT severity score index and its relation to age, sex, and PCR test results

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Publication Date
Wed Sep 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Study of Forward Osmosis Using Various Drawing Agent
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This research was aimed to study the osmotic efficiency of the draw solutions and the factors affecting the performance of forward osmosis process : The draw solutions used were magnesium sulfate hydrate (MgSO4.7H2O) pojtassium chloride (KCL), calcium chloride (CaCl2) and ammonium bicarbonate (NH4HCO3). It was found that water flux increases with increasing draw solution concentration, and feed solution flow rate and decreases with increasing draw solution flow rate and feed solution concentration. And also found that the efficiency of the draw solutions is in the following order:

CaCl2> KCI > NH4HCO3> MgSO4.7H

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Wellbore Breakouts Prediction from Different Rock Failure Criteria
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One of the wellbore instability problems in vertical wells are breakouts in Zubair oilfield. Breakouts, if exceeds its critical limits will produce problems such as loss circulation which will add to the non-productive time (NPT) thus increasing loss in costs and in total revenues. In this paper, three of the available rock failure criteria (Mohr-Coulomb, Mogi-Coulomb and Modified-Lade) are used to study and predict the occurrence of the breakouts. It is found that there is an increase over the allowable breakout limit in breakout width in Tanuma shaly formation and it was predicted using Mohr-Coulomb criterion. An increase in the pore pressure was predicted in Tanuma shaly formation, thus; a new mud weight and casing pr

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Telecom Churn Prediction based on Deep Learning Approach
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      The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Network Traffic Prediction Based on Time Series Modeling
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    Predicting the network traffic of web pages is one of the areas that has increased focus in recent years. Modeling traffic helps find strategies for distributing network loads, identifying user behaviors and malicious traffic, and predicting future trends. Many statistical and intelligent methods have been studied to predict web traffic using time series of network traffic. In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression, and Random Forest), and comparing the performance of the models using (SMAPE) and

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