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Development of gravitational search algorithm model for predicting packing density of cementitious pastes
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Evaluation of a fire safety risk prediction model for an existing building
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Abstract<p>Fire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20</p> ... Show More
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Publication Date
Sun May 24 2026
Journal Name
Misan Journal For Physical Education Sciences
The impact of three models of training load on the development of the maximum strength for elite boxers
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Publication Date
Sun Sep 02 2018
Journal Name
Arab Journal Of Basic And Applied Sciences
Development of the Banach contraction method for the solution of nonlinear thin film flows of non-Newtonian fluids
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Publication Date
Sun May 24 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The multi-detector computed tomographical analysis of bone density in impacted maxillary canines
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Background: Maxillary canines are important aesthetically and functionally, but impacted canines are more difficult and time consuming to treat, the aim of this study is to investigate with multi-detector computed tomography the correlation between the bone density and the upper canine impaction. Material and method: A sample of Unilaterally impacted maxillary canines from 24 patients (19 female, 5 male) who were referred to accurately localize the impacted canines at al- Karkh general hospital were evaluated by a volumetric 3-d images by the multi-detector computed tomography to accurately measure the bone density of the maxillary cortical palate of the maxillary impacted canine side and compare it with the other side of the normally erupt

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Publication Date
Mon Aug 20 2018
Journal Name
Physical Review E
Dynamical density-functional-theory-based modeling of tissue dynamics: Application to tumor growth
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Publication Date
Fri Sep 30 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Thermal and Catalytic Degradation Kinetics of High-Density Polyethylene Over NaX Nano-Zeolite
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Thermal and catalytic pyrolysis of waste plastics in an inert atmosphere has been regarded as a creative method, since pyrolysis can convert plastics waste into hydrocarbons that can be used either as fuels or as a source of chemicals.

Natural Iraqi kaolin clay was used to synthesis the NaX nano- zeolite by hydrothermal conditions with average particle size equal to 77.63nm.Thermal decomposition kinetics of high-density polyethylene (HDPE) in the absence and presence of catalysts nano NaX Zeolite was investigated. Thermal and catalytic degradation of HDPE was performed using a thermogravimetric analyzer in nitrogen atmosphere under non-isothermal conditions 4, 7 and 10 °C/min heating rates were employed in thermogravimetric anal

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Publication Date
Thu Aug 31 2017
Journal Name
Pramana
Matter density distributions and elastic form factors of some two-neutron halo nuclei
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The Skyrme–Hartree–Fock (SHF) method with MSK7 Skyrme parameter has been used to investigate the ground-state properties for two-neutron halo nuclei 6He, 11Li, 12Be and 14Be. These ground-state properties include the proton, neutron and matter density distributions, the corresponding rms radii, the binding energy per nucleon and the charge form factors. These calculations clearly reveal the long tail characterizing the halo nuclei as a distinctive feature.

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