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jeasiq-1923
Comparison of weighted estimated method and proposed method (BEMW) for estimation of semi-parametric model under incomplete data
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Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the parametric part, a method has been developed to estimate the parametric of the partial linear regression model represented by weighted estimators as well as by the suggested method (EMBW). Two methods of the simulation were compared using three sizes (n = 100,150,200) and using three different values for and zero mean and it was found that the proposed method (EMBW) was superior to the weighted estimator method.

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Publication Date
Thu Jun 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Theoretical Calculations of the Electron Transport Parameters in CH4-Ar and CH4-Ne Mixtures Gases Using Monte Carlo Method
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    The result of concentration varying of mixture methane with argon and neon gas are believed to study the change in electrons energy distribution function and then the change of the electrons transport parameters including the drift velocity, the mean energy, characteristics energy and diffusion coefficient. In the present work,a contemporary developed computer, simulation program known as Bolsig+ is being used for calculating the electron transport parameters.
 

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Data Acquisition System for Wind Speed, Direction and Temperature Measurements
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This paper describes the use of microcomputer as a laboratory instrument system. The system is focused on three weather variables measurement, are temperature, wind speed, and wind direction. This instrument is a type of data acquisition system; in this paper we deal with the design and implementation of data acquisition system based on personal computer (Pentium) using Industry Standard Architecture (ISA)bus. The design of this system involves mainly a hardware implementation, and the software programs that are used for testing, measuring and control. The system can be used to display the required information that can be transferred and processed from the external field to the system. A visual basic language with Microsoft foundation cl

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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
L-pre- and L-semi-P- compact Spaces
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The purpose of this paper is to study a new types of compactness in the dual bitopological spaces. We shall introduce the concepts of L-pre- compactness and L-semi-P- compactness .

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Publication Date
Tue Nov 13 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
WE-Prime Submodules and WE-Semi-Prime Submodules
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"In this article, "we introduce the concept of a WE-Prime submodule", as a stronger form of a weakly prime submodule". "And as a "generalization of WE-Prime submodule", we introduce the concept of WE-Semi-Prime submodule, which is also a stronger form of a weakly semi-prime submodule". "Various basic properties of these two concepts are discussed. Furthermore, the relationships between "WE-Prime submodules and weakly prime submodules" and studied". "On the other hand the relation between "WE-Prime submodules and WE-Semi-Prime submodules" are consider". "Also" the relation of "WE-Sime-Prime submodules and weakly semi-prime submodules" are explained. Behind that, some characterizations of these concepts are investigated".

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Publication Date
Mon Sep 16 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Approximaitly Semi-Prime Submodules and Some Related Concepts
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    We introduce in this paper the concept of approximaitly semi-prime submodules of unitary left -module  over a commutative ring  with identity as a generalization of a prime submodules and semi-prime submodules, also generalization of quasi-prime submodules and approximaitly prime submodules. Various basic properties of an approximaitly semi-prime submodules are discussed, where a proper submodule  of an -module  is called an approximaitly semi-prime submodule of  , if whenever , where ,  and , implies that . Furthermore the behaviors of approximaitly semi-prime submodule in some classes of modules are studied. On the other hand several characterizations of this concept are

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Publication Date
Sun Aug 01 2021
Journal Name
Telkomnika
Proposed different relay selection schemes for improving the performance of cooperative wireless networks
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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Wed Jun 01 2022
Journal Name
Res Militaris
Building the proposed Fama and French Six-Factor Model FF6M-DLE by adding the indebtedness factor and its reflection on the fair value of common stock
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The research aims to determine the required rate of return according to the Fama and French five-factor model, after strengthening it by adding the indebtedness factor to build the Fama and French six-factor model FF6M-DLE. The effect of the indebtedness factor on the company's profitability and the real value of the ordinary shares calculated according to the (equivalent ascertainment) model and its suitability with the company's situation, and an analysis of the fluctuation between the market value and the real value of the ordinary stocks.

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Publication Date
Sun Jan 01 2017
Journal Name
Statistical Applications In Genetics And Molecular Biology
Mixture model-based association analysis with case-control data in genome wide association studies
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Abstract<p>Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d</p> ... Show More
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