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Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others in most simulation scenarios according to the integrated mean square error and integrated classification error

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and analyzing the demand function for agricultural imports in Iraq for the period (1980-2012) in Autoregressive Distributed Lag Model(ARDL)
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Abstract:

The issues related to foreign trade is a broad field for discussions and captures the interest of economists for their contribution to the process of economic development in the economies of the countries, especially developing ones. The imports of goods and services in foreign trade constitute an important part of the local by which the economy gets goods and services that the economy cannot produce because of the incompetent base of production. Further, the demand function of imports occupied a good deal of the attention of researchers in the field of international economics for which agricultural imports constitute an important part. The reason for the interest in the subject is due to its im

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Samples of Al Samarqandi’s Selection in some of Washing Laws and the touch of the Grecians Quran in his book (The scholars’ Masterpiece)
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The Research is interested in the detailed comparative study of certain selection of
Imam Alsamarqandi in some subjects of washing and touching the Gracious Quran.
The value of this study is that it is related to one aspect of the duties obliged on Muslim
like parity.
The study has tried to collect certain scholars’ opinions of eight doctrines with the
selection of Alsamarqandi to make a comp arson between them and to show how
Alsamarqandi is able to create legal laws from his sources to lead the researchers nto have
knowledge about the syllabi of the famous scientists.
Finally we ask God to bless to what is right and to accept this study and make it part of
our good deeds, Ameen.

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Three Weighted Residuals Methods for Solving the Nonlinear Thin Film Flow Problem
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Abstract<p>In this paper, the methods of weighted residuals: Collocation Method (CM), Least Squares Method (LSM) and Galerkin Method (GM) are used to solve the thin film flow (TFF) equation. The weighted residual methods were implemented to get an approximate solution to the TFF equation. The accuracy of the obtained results is checked by calculating the maximum error remainder functions (MER). Moreover, the outcomes were examined in comparison with the 4<sup>th</sup>-order Runge-Kutta method (RK4) and good agreements have been achieved. All the evaluations have been successfully implemented by using the computer system Mathematica®10.</p>
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Publication Date
Fri Apr 21 2023
Journal Name
Aip Conference Proceedings
Efficient computational methods for solving the nonlinear initial and boundary value problems
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In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Traditional and molecular methods for diagnosing bacterial meningitis in Erbil city, Iraq
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Bacterial meningitis is a leading cause of illness and death worldwide. It is crucial for clinical and public health care, as well as disease control, to identify the meningitis-causing agent promptly. Between June 2021-February 2022, a total of 100 cerebrospinal fluid (CSF) and blood samples were collected from suspected cases of meningitis admitted to Raparin Paediatric Teaching Hospital, Erbil city-Iraq. Cytochemical, cultural, and biochemical tests were conducted, and confirmed by molecular techniques. Bacterial culture findings were positive in 7% of CSF samples and just one positive among blood samples. The most common pathogens found by cultural characteristics and VITEK 2 Compact System were Staphylococcus sciuri in two

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Efficient computational methods for solving the nonlinear initial and boundary value problems
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Publication Date
Wed Apr 15 2020
Journal Name
Al-mustansiriyah Journal Of Science
Adaptation Proposed Methods for Handling Imbalanced Datasets based on Over-Sampling Technique
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Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of King Saud University - Science
Three iterative methods for solving second order nonlinear ODEs arising in physics
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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of human development indicators in the context of distributive justice for Iraq for the period 2003-2013
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Abstract                                                                             

The government spending in Iraq and witnessed the changes and developments, especially after 2003, which outweighed consumer spending at the expense of capital expenditure and increased support and diversity of trends towards improving pension conditions for member

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