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Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

      For estimating the conditional regression model in the analysis of environment pollution as a function of oil production and environmental factors using the generalized estimating equation (GEE) in the formulation of inference methods that facilitate the conditional logistic regression model taking advantage of the actual correlations between responses in the data, as well as the specific correlation structure through robust sandwich estimators (RSE) as well as application many of various model selection criteria. Because the efficiency of estimates is contingent on the working correlation matrix specification, the appropriate selection of a working correlation matrix can significantly advance the GEE statistical inference efficiency. After comparing the performance of specific criteria indicating that QIC is the selection criterion that is most suited for GEE method. The application results showed that QIC had the lowest information loss in GEE method in which the objective to develop a predictive model of the candidate set, Through this research, condition logistic regression has also been demonstrated to be an effective tool that can be used in other studies to explore the relationships between response and explanatory variables.

 

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Numerical Solution for Linear Fredholm Integro-Differential Equation Using Touchard Polynomials
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A new method based on the Touchard polynomials (TPs) was presented for the numerical solution of the linear Fredholm integro-differential equation (FIDE) of the first order and second kind with condition. The derivative and integration of the (TPs) were simply obtained. The convergence analysis of the presented method was given and the applicability was proved by some numerical examples. The results obtained in this method are compared with other known results.

 

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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Efficient approach for solving high order (2+1)D-differential equation
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Publication Date
Sun Jun 07 2026
Journal Name
Sciences Journal Of Physical Education
Leadership patterns for university student activities managers according to the Blake and Moton model (The managerial Grid)
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The researcher is one of the workers in university sports student activities, as he noticed that there is a diversity in the use of leadership patterns among managers of student activities in Iraqi universities between one director and another, which leads to the impact of these leadership styles on performance, positive or negative, in the level of human relations and the achievement of results. The researcher adopted the descriptive method in the survey method with relational relationships. The research sample consisted of (184) sports coaches who represent (27) universities and governmental and private colleges. To achieve the research objectives, the researcher used the Statistical Package for Social Sciences (Spss). To extract.statisti

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Comparison among variable selection models and its application to health dataset
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Newton-Kantorovich Method for Solving One of the Non-Linear Sturm-Liouville Problems
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Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl

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Publication Date
Sat Sep 01 2007
Journal Name
Al-khwarizmi Engineering Journal
A Fully Computerized Method to Backup the Router Configuration File
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This paper presents a fully computerized method to backup the router configuration file. The method consists of a friendly graphical interface programmed by Java programming language.

    The proposed method is compared with the two existing methods, namely: TFTP server method and Copy/Paste method. The comparison reveals that the proposed method has many advantages over the existing ones. The proposed method has been implemented on Cisco routers (series 2500, 2600 and 2800).

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Suggested method for modifying the site parameter
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     Estimating multivariate location and scatter with both affine equivariance and positive break down has always been difficult. Awell-known estimator which satisfies both properties is the Minimum volume Ellipsoid Estimator (MVE) Computing the exact (MVE) is often not feasible, so one usually resorts to an approximate Algorithm. In the regression setup, algorithm for positive-break down estimators like Least Median of squares typically recomputed the intercept at each step, to improve the result. This approach is called intercept adjustment. In this paper we show that a similar technique, called location adjustment, Can be applied to the (MVE). For this purpose we use the Minimum Volume Ball (MVB). In order

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Study of the Symmetry Energy and the Nuclear Equation of State for 13O -13B and 13N-13C Mirror Nuclei
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In parallel with the shell model using the harmonic oscillator's single-particle wave functions, the Hartree-Fock approximation was also used to calculate the neutron skin thickness, the mirror charge radii, and the differences in proton radii for 13O-13B and 13N-13C mirror nuclei. The calculations were done for both mirror nuclei in the psdpn model space. Depending on the type of potential used, the calculated values of skin thickness are affected. The symmetry energy and the symmetry energy's slope at nuclear saturation density were also determined, and the ratio of the density to the saturation density of nuclear matter and the symmetry energy has a nearly linear correlation. The mirror ener

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