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INNOVATE GESTATIONAL AGE ESTIMATION MODEL FOR IRAQI FETUSES BASED ON ULTRASOUND IMAGES MEASUREMENTS
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Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify for Iraqi population and leading to some error in GA estimation results, so the objective of this study is to innovate GA estimation model for Iraqi people. This study was performed in the department of Obstetrics and Gynecology in Al- Yarmouk Teaching Hospital and AL- Alawiya Teaching Hospital in Baghdad, Iraq, during 2019 on 200 pregnant women of singleton and normal pregnancies, fetal GA (20-40) weeks (W). The obtained dataset (fetal biometry), were utilized to create GA estimation model in Iraq using IBM SPSS Version 23 software package (IBM^® Software). The statistical analysis of proposed GA model showed, the correlation (R) of model is 0.987 it is very high value and this is a good result to obtain the best regression model. as well as the Std error of Estimation was 0.61095 this is very small value and indicate the best result. The significant of model P=0.000 That means the model, as a whole, is a significant fit to the data (because P < 0.05).

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression based on Non-Linear Polynomial Prediction Model
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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Data Hiding in 3D Model Based on Surface Properties
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    Data hiding strategies have recently gained popularity in different fields; Digital watermark technology was developed for hiding copyright information in the image visually or invisibly. Today, 3D model technology has the potential to alter the field because it allows for the production of sophisticated structures and forms that were previously impossible to achieve. In this paper, a new watermarking method for the 3D model is presented. The proposed method is based on the geometrical and topology properties of the 3D model surface to increase the security. The geometrical properties are based on computing the mean curvature for a surface and topology based on the number of edges around each vertex, the vertices

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Gestational Diabetes Mellitus and Hormonal Alteration
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Gestational Diabetes Mellitus is known as carbohydrate intolerance first detected during pregnancy. Pregnancy is periods of intense hormonal changes. The aim of the present study was to investigate a possible relation between the changes in serum hormones such as Luteinizing hormone (LH) , follicle stimulating hormone(FSH), Progesterone, and Prolactin with gestational diabetes mellitus. Thirty patients with gestational diabetes mellitus aged (22 -40) year attending the national center for treatment and research of diabetes/ AL-Mustansiriya University in Baghdad and 29 controls aged (20-39) year were participated. Hormonal tests including, FSH, LH, Progesterone, and Prolactin were detected by using Enzyme Linked Fluorescent Assay (ELFA) k

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economic And Administrative Science
On Shrinkage Estimation for Generalized Exponential Distribution
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
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Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR).

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Publication Date
Tue Mar 01 2022
Journal Name
Results In Engineering
Predictive model for stress at ultimate in internally unbonded steel tendons based on genetic expression programming
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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimation of a Circular Regression Model on Peak Systolic Blood Pressure Data
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Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

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Publication Date
Sun Jul 02 2023
Journal Name
Iraqi Journal Of Science
Comparison of Ionospheric Total Electron Content Measurements with IRI- 2012 Model Predictions Over Athens
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Total Electron Content measurements derived from Athens station ionograms (ITEC),
located near Iraq, during the ascending phase of solar cycle 24 (July 2009- April 2010),
according to availability of data, are compared with the latest version of the International
Reference Ionosphere model, IRI-2012 (IRI TEC), using two options (NeQuick, IRI01-
Corr) for topside electron density.
The results obtained from both (ITEC and IRI TEC) techniques were similar, where
correlation coefficients between them are very high. Generally, the IRI predictions
overestimate the ITEC values.

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Heart Disease Classification–Based on the Best Machine Learning Model
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    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

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Scopus (12)
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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
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