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Software Development for First Aid Decision Support System
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This work presents an approach to deal with modelling a decision support system framework to introduce an application for decisions in medical knowledge system analysis. First aid is extremely important worldwide and, hence, a decision support framework, know as First Aid Decision Support System (FADSS), was designed and implemented to access experimental cases exerting danger to the general population, offering advanced conditions for testing abilities in research and arranging an emergency treatment through the graphical user interface (UI). The design of first aid treatment in FADSS depends on the general cases in first aid. We presented a strategy to manage first aid treatment  by modelling an application (FADSS) that assists people in finding information about first aid cases that are available as an application service. FADSS service uses a set of 15 important situations that might happen to people. The decision for treatment is suggested on the system for a different accident. FADSS tests the information in real-time by using mathematical models, decision tree and data mining (C4.5 algorithm) that are used in this research to build a decision making system. The system automatically sends warnings when the case is very critical, using text messages as email reports. The main objective of this study is to provide an efficient tool that helps people and junior workers in first aid centres in order to find the available resources of information.

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Applying Ensemble Classifier, K-Nearest Neighbor and Decision Tree for Predicting Oral Reading Rate Levels
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For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Modified Multi-Criteria Decision Making Methods to Assess Classification Methods
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      During the last few decades, many academic and professional groups gave attention to adopting the multi-criteria decision-making methods in a variety of contexts for decision-making that are given to the diversity and sophistication of their selections. Five different classification methods are tested and assessed in this paper. Each has its own set of five attribute selection approaches. By using the multi-criteria decision-making procedures, these data can be used to rate options. Technique for order of preference by similarity to ideal solution (TOPSIS) is designed utilizing a modified fuzzy analytic hierarchy process (MFAHP) to compute the weight alternatives for TOPSIS in order to obtain the confidence value of each class

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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Design of Expert System for Managing the System of AthTharthar Lake
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The operation and management of water resources projects have direct and significant effects on the optimum use of water. Artificial intelligence techniques are a new tool used to help in making optimized decisions, based on knowledge bases in the planning, implementation, operation and management of projects as well as controlling flowing water quantities to prevent flooding and storage of excess water and use it during drought.

 In this research, an Expert System was designed for operating and managing the system of AthTharthar Lake (ESSTAR). It was applied for all expected conditions of flow, including the cases of   drought, normal flow, and during floods. Moreover, the cases of hypothetical op

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Financial analysis indicators and their impact on investment decision-making: for the national insurance company (applied research)
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The financial analysis of the published financial statements is the means that enables businessmen, financial institutions, financial analysts and others to conduct their studies and conclusions to obtain information that helps them in the decision-making process, including decisions related to investment. National in making the decision on the investment activity, for the period from 2012 to 2018, through the information provided by the annual financial statements, by selecting a set of indicators provided by the financial statements, namely (liquidity ratio, activity percentage, profitability ratios) to measure the extent of this ability Indicators in determining their role in making an investment decision.

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Matrix Form of Deriving High Order Schemes for the First Derivative
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For many problems in Physics and Computational Fluid Dynamics (CFD), providing an accurate approximation of derivatives is a challenging task. This paper presents a class of high order numerical schemes for approximating the first derivative. These approximations are derived based on solving a special system of equations with some unknown coefficients. The construction method provides numerous types of schemes with different orders of accuracy. The accuracy of each scheme is analyzed by using Fourier analysis, which illustrates the dispersion and dissipation of the scheme. The polynomial technique is used to verify the order of accuracy of the proposed schemes by obtaining the error terms. Dispersion and dissipation errors are calculated

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Arabic Cyberbullying Detection Using Support Vector Machine with Cuckoo Search
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      Cyberbullying is one of the biggest electronic problems that takes multiple forms of harassment using various social media. Currently, this phenomenon has become very common and is increasing, especially for young people and adolescents. Negative comments have a significant and dangerous impact on society in general and on adolescents in particular. Therefore, one of the most successful prevention methods is to detect and block harmful messages and comments. In this research, negative Arabic comments that refer to cyberbullying will be detected using a support vector machine algorithm. The term frequency-inverse document frequency vectorizer and the count vectorizer methods were used for feature extraction, and the results wer

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Publication Date
Thu Jun 09 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The financial aid of the Central Bank of Iraq to the government and its reflection on indicators of banking stability/ Applied Research
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The research aims to define the images of financial aid that it provides within their tasks (central banks to governments) and how it can affect the indicators of banking stability, as well as monitoring the levels of banking stability in the Iraqi economy through the indicators used by the Central Bank of Iraq, and the importance of research in banking stability lies in Iraq, because any decrease in the movement of the aggregate banking stability index will reflect negatively on the financial sector in Iraq. Therefore, the Central Bank sought to provide financial aid to the government through a group of components, some of which are represented by initiatives that contribute to revitalizing the national economy and the other hel

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Publication Date
Sun Sep 01 2019
Journal Name
Al-dhad Book Store
Multivariate Analysis - First Edition
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This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

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Publication Date
Fri Feb 01 2019
Journal Name
Al-dhad - Book Store And Publishing
Multivariate Analysis (First Edition)
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This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

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