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Performance Evaluation of Al-Karkh Water Treatment Plant Using Model-driven and Data-Driven Models
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Abstract<p>There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardness, Calcium, Magnesium, Total Solids, Nitrite, Nitrates, Ammonia, and Silica are to be used to construct the specific model, while pH, Fluoride, Aluminium, Nitrite, Nitrate, Ammonia, Silica, and Orthophosphate of the treated water were eliminated from the analysis. For modeling the coagulation and flocculation process temperature, Alkalinity and pH of raw water were the depended variables of the model. As for the modeling process turbidity of the treated water was used as the output variable. In general, the linear models including model-driven type, (Multivariate multiple regression, MMR and Multiple linear regression, MLR) have slightly higher prediction efficiencies than the, data-driven type (artificial neural network, ANNM). The coefficients of determination (R<sup>2</sup>) reached 66 to 85% for the MMR and MLR models and 65 to 81% for the ANN models.</p>
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Publication Date
Fri Dec 30 2011
Journal Name
Al-kindy College Medical Journal
Outcome of surgical treatment of highgrade intramedullary astrocytomas
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Background: Intramedullary astrocytomas
account for about 1% of all CNS tumors and
6–8% of spinal cord tumors. The vast majority
of intramedullary astrocytomas are slowgrowing
lesions.
Objectives: The goal in this study was to
review a series of patients who underwent
surgical removal of intramedullary high-grade
astrocytomas, focusing on the functional
outcome and the effect of multimodality
treatment on the survival of patients with high
grade intramedullary astrocytoma.
Methods: Between June 1999 and June 2004,
22 patients underwent removal of
intramedullary high-grade astrocytomas in four
neurosurgical hospital in Baghdad/ Iraq
(Neurosurgical hospital, Al Shaheed Adnan
Hospital for

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archives
Morpho-physiological study on the effect of lead stress and selenium foliar application on growth of dill plant anethum graveolens l
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The experiment was carried out in the green house of botanical garden belong to Department of Biology/College of Education for Pure Science Ibn AL-Haitham, University of Baghdad for growing season 2017-2018 to evaluate effect of lead stress with concentrations (0, 50, 100, 150) mg.L -1 and Selenium concentrations (0, 15, 30) mg.L-1 on growth of dill plant using pots. The experiment was designed according to completely randomized design (CRD) with three replications. Result indicated that dill plants subjected to lead stress with height concentrations caused decrease in plant parameters (plant height, no. of branches. plant-1, root length, shoot dry weight, the content of nitrogen, phosphorus and potassium, protein concentration, no. of umbe

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Wed Apr 28 2021
Journal Name
Misan Journal For Physical Education Sciences
The Effectiveness of Using Generative Learning Model in Learning Kinetic Series on Rings and Horizontal Bar In Artistic Gymnastics for men
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The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

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Publication Date
Mon Mar 29 2021
Journal Name
Journal Of Engineering
Extracting Four Solar Model Electrical Parameters of Mono-Crystalline Silicon (mc-Si) and Thin Film (CIGS) Solar Modules using Different Methods
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Experimental measurements were done for characterizing current-voltage and power-voltage of two types of photovoltaic (PV) solar modules; monocrystalline silicon (mc-Si) and copper indium gallium di-selenide (CIGS). The conversion efficiency depends on many factors, such as irradiation and temperature. The assembling measures as a rule cause contrast in electrical boundaries, even in cells of a similar kind. Additionally, if the misfortunes because of cell associations in a module are considered, it is hard to track down two indistinguishable photovoltaic modules. This way, just the I-V, and P-V bends' trial estimation permit knowing the electrical boundaries of a photovoltaic gadget with accuracy. This measure

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Publication Date
Mon Mar 11 2019
Journal Name
Al-khwarizmi Engineering Journal
An Investigation Study of Tool Geometry in Single Point Incremental Forming (SPIF) and their effect on Residual Stresses Using ANOVA Model
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Incremental forming is a flexible sheet metal forming process which is performed by utilizing simple tools to locally deform a sheet of metal along a predefined tool path without using of dies. This work presents the single point incremental forming process for producing pyramid geometry and studies the effect of tool geometry, tool diameter, and spindle speed on the residual stresses. The residual stresses were measured by ORIONRKS 6000 test measuring instrument. This instrument was used with four angles of (0º,15º,30º, and 45º) and the average value of residual stresses was determined, the value of the residual stress in the original blanks was (10.626 MPa). The X-ray diffraction technology was used to measure the residual stresses

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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Publication Date
Mon Mar 27 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Evaluation of Cefixime Nanocrystals
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Drug nanocrystals are nanoscopic crystals of the parent compound with dimensions less than 1 µm. A decrease in particle size will lead to an increase in effective surface area in the diffusion layer, which, in turn, increases the drug dissolution rate. Drug nanocrystals are one of the most important strategies to enhance the oral bioavailability of hydrophobic drugs.

Cefixime is the first member of what is generally termed the third generation orally active cephalosporins. These third generation cephalosporins are distinct from the older β-lactam antibiotics in their intensive antibacterial activity against a wide range of gram-negative bacteria.

The aim of this study is to prepare nanocrystals of cefixime as a caps

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Publication Date
Sun Jun 03 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Evaluation of Acyclovir Microspheres
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The present study is to formulate and evaluate Acyclovir (ACV) microspheres using natural polymers like chitosan and sodium alginate. ACV is a DNA polymerase inhibitor used in treating herpes simplex virus infection and zoster varicella infections. Acyclovir is a suitable candidate for sustained-release (SR) administration as a result of its dosage regimen twice or thrice a day and relatively short plasma half-life (approximately 2 to 4 hours). Microspheres of ACV were prepared by an ionic dilution method using chitosan and sodium alginate as polymers. The prepared ACV microspheres were then subjected to FTIR, SEM, particle size, % yield, entrapment efficiency, in vitro dissolution studies and release kinetics mechanism. The FTI

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Evaluation of Ezetimibe Nanoparticles
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The aim of this study is to formulate and evaluate ezetimibe nanoparticles using solvent antisolvent technology. Ezetimibe is a practically water-insoluble drug which acts as a lipid lowering drug that selectively inhibits the intestinal absorption of cholesterol and related phytosterols. Ezetimibe prepared as nano particles in order to improve its solubility and dissolution rate.

Thirty formulas were prepared and different stabilizing agents were used with different concentrations such as poly vinyl pyrrolidone (PVPK-30), poly vinyl alcohol (PVA), hydroxy propyl methyl cellulose E5 (HPMC), and poloxamer. The ratios of drug to stabilizers used to prepare the nanoparticles were 1: 2, 1:3 and 1:4.

The prepared nanoparticles

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