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Using count regression models to investigate the most important economic factors affecting divorce in Iraq
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The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemployment rate, inflation and Gini coefficient. The data were taken from the website of the Statistics Center for the years 2002 to 2023.Under the Poisson regression model, each factor has been reported to have an effect on the divorce rate. The two factors of inflation and unemployment had a direct effect and income inequality factors had an inverse effect on the divorce rate. But, under the negative binomial regression model, only inflation has an effect on the number of divorces. It is worth noting that according to the AIC values, the negative binomial regression model has a better fit than the Poisson regression model because its AIC value is lower.

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some methods for estimating the parameters of the binary logistic regression model using the genetic algorithm with practical application
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Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and Analyzing of the Relationship between the Financial Development, Economic growth, and Poverty in Iraq with the Autoregressive Distributed lag Model framework for the period (1980-2010)
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The developed financial system is essential for increasing economic growth and poverty reduction in the world. The financial development helps in poverty reduction indirectly via intermediate channel which is the economic growth. The financial development enhancing economic development through mobilization of savings and channel them to the most efficient uses with higher economic and social returns. In addition, the economic growth reduces the poverty through two channels. The first is direct by increasing the introduction factors held by poor and improve the situations into the sectors and areas where the poor live. The second is indirect through redistribution the realized incomes from the economic growth as well as the realiz

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Publication Date
Mon Mar 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Prevalence of self-reported halitosis and associated factors in 15 years old male students in Karbala City-Iraq
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Background׃ Halitosis is a common condition and is most often caused by a buildup of bacteria in the mouth because of gum disease, food, or plaque. It can result in anxiety among those affected, it is also associated with depression and symptoms of obsessive compulsive disorder. The aim of this study isto assess the prevalence of self-reported halitosis and associated factors (dental plaque, gingival condition and dental caries) in 15 years old male students in Karbala city in Iraq. Additionally, we studied adolescents’ concern with their own breath and whether anyone had ever told them that they had halitosis. Methods׃ A cross sectional observational survey was conducted to15 years old high school students from public and p

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Publication Date
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.
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The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Scopus
Publication Date
Thu Aug 01 2024
Journal Name
The American Journal Of Management And Economics Innovations
THE ROLE OF ECONOMIC DATA ANALYSIS IN MANAGING MEDIUM AND SMALL COMPANIES TO MAKE STRATEGIC DECISIONS AND IMPROVE PERFORMANCE: AN ANALYTICAL STUDY
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Economic analysis plays a pivotal role in managerial decision-making processes. This analysis is predicated on deeply understanding economic forces and market factors influencing corporate strategies and decisions. This paper delves into the role of economic data analysis in managing small and medium-sized enterprises (SMEs) to make strategic decisions and enhance performance. The study underscores the significance of this approach and its impact on corporate outcomes. The research analyzes annual reports from three companies: Al-Mahfaza for Mobile and Internet Financial Payment and Settlement Services Company Limited, Al-Arab for Electronic Payment Company, and Iraq Electronic Gateway for Financial Services Company. The paper concl

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
Factors Influence the Development of Dysrhythmia after Acute Myocardial Infarction in Patients Admitted to CCU of Alkindy Teaching Hospital
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Objective The incidence of rhythm and conduction abnormalities during acute myocardial infarction may approaches 100%; most are seen during the pre-hospital and coronary care unit phases, leading to deleterious effect on morbidity and mortality, this study conducted to find important persistent dysrhythmia found during CCU admission of acute myocardial infarction patients.Method A retrospective observational study of 553 patients who were admitted to the Coronary Care Unit of Alkindy Teaching Hospital during Year 2011 with diagnosis of acute myocardial infarction, Information and data extracted from case sheets and associated 12 leads daily ECGsResults only 25% of our patients had dysrhythmia on examining the present 12 leads ECGs , the

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Scientific & Engineering Research
Horizontal Fragmentation for Most Frequency Frequent Pattern Growth Algorithm
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Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agriculture And Statistical Science
COMPARISON OF FORECASTING OF THE RISK OF CORONAVIRUS (COVID-19) IN HIGH-QUALITY AND LOW-QUALITY HEALTHCARE SYSTEMS, USING ANN MODELS
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COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce

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Scopus
Publication Date
Sun Nov 01 2020
Journal Name
2020 8th Ieee Ras/embs International Conference For Biomedical Robotics And Biomechatronics (biorob)
Estimating Wrist Joint Torque Using Regression Ensemble of Bagged Trees under Multiple Wrist Postures
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Publication Date
Thu Mar 29 2018
Journal Name
Construction Research Congress 2018
Validation of Time-Safety Influence Curve Using Empirical Safety and Injury Data—Poisson Regression
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