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Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Water harvesting and sustainable spatial development A case study of the province of badra – zurbatiyah
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The major climate changes that have affected the planet in addition to wave the big drought plaguing the study area, including the lack of water for imports Badra River fatigue because of the Iran constructing dams on this river and make use of the waters for the benefitof its territory. The subject of finding sources of water has become available with the possibility of exploiting them in an exemplary manner is one of the key things in order to be exploited somewhere.
The study area was chosen within the eastern border of the province of Wasit within the district of Badra border, an area of (1557.5 km2) almost "to study the characteristics of hydrological and identify possibilities for water harvesting them. In this study was conduct

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Publication Date
Sun Sep 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
New Development in the Process for the Production of Polybutadiene Rubber
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Publication Date
Mon Sep 09 2024
Journal Name
Научный Форум
the functioning of artificial intelligence for the development of communication skills among foreigners learning Russian
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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Development of Green Method for Trace Determination of Bendiocarb in Real Samples Using Emerson
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In this study, cloud point extraction combined with molecular spectrometry as an eco-friendly method is used for extraction, enrichment and determination of bendiocarb (BC) insecticide in different complex matrices. The method involved an alkaline hydrolysis of BC followed Emerson reaction in which the resultant phenol is reacted with 4-aminoantipyrene(4-AAP) in the presence of an alkaline oxidant of potassium ferric cyanide to form red colored product which then extracted into micelles of Triton X-114 as a mediated extractant at room temperature. The extracted product in cloud point layer is separated from the aqueous layer by centrifugation for 20 min and dissolved in a minimum amount of a mixture ethanol: water (1:1) followed

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Publication Date
Mon Feb 13 2023
Journal Name
International Journal Of Professional Business Review
The Reality of Local Investment in Iraq and Prospects for its Development: a Case Study in the Baghdad Investment Commission
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Purpose: This research is to identify the most important challenges for the local investment commissions and to develop solutions and proposals to encourage local and foreign investment in local governments in Iraq (the Iraqi provinces are irregular in the region).   Theoretical Framework: This research suggests a conceptual framework for the local investment commissions in order to solve their problems, the most important of which was to identify the most critical challenges which are facing the Baghdad Investment Commission BIC and how to overcome them.   Design/The methodology approach: Research involved a mixed-methods approach through two stages. During the first stage, the researcher gathered quantitative data from all inves

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Implementation of Machine Learning Techniques for the Classification of Lung X-Ray Images Used to Detect COVID-19 in Humans
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COVID-19 (Coronavirus disease-2019), commonly called Coronavirus or CoV, is a dangerous disease caused by the SARS-CoV-2 virus. It is one of the most widespread zoonotic diseases around the world, which started from one of the wet markets in Wuhan city. Its symptoms are similar to those of the common flu, including cough, fever, muscle pain, shortness of breath, and fatigue. This article suggests implementing machine learning techniques (Random Forest, Logistic Regression, Naïve Bayes, Support Vector Machine) by Python to classify a series of chest X-ray images that include viral pneumonia, COVID-19, and healthy (Not infected) cases in humans. The study includes more than 1400 images that are collected from the Kaggle platform. The expe

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Benchmarking Framework for COVID-19 Classification Machine Learning Method Based on Fuzzy Decision by Opinion Score Method
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     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Sun Jan 26 2025
Journal Name
Journal Of Engineering
Computational Method for Unsteady Motion of Two-Dimensional Airfoil
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A numerical method is developed for calculation of the wake geometry and aerodynamic forces on two-dimensional airfoil under going an arbitrary unsteady motion in an inviscid incompressible flow (panel method). The method is applied to sudden change in airfoil incidence angle and airfoil oscillations at high reduced frequency. The effect of non-linear wake on the unsteady aerodynamic properties and oscillatory amplitude on wake rollup and aerodynamic forces has been studied. The results of the present method shows good accuracy as compared with flat plate and for unsteady motion with heaving and pitching oscillation the present method also shows good trend with the experimental results taken from published data. The method shows good result

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