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jperc-1019
Comparison between Rush Model Parameters to Completed and Lost Data by Different Methods of Processing Missing Data
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The current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1st, 2nd and 3rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition, the researcher relied on chi-squared value for each item at (0.05).  After that, the researcher found out the parameters of the missing data after relying on a loss percentage (10%) and used three ways to treat them (mean, regression, likelihood). The results showed that the comparison between the parameters completed and missing data by using three ways of processing the missing data is in favor of the parameters of the completed data, and the likelihood way is the suitable way to treat the completed data. 

     The conclusions, recommendations and suggestions have been drawn based on the findings.

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Publication Date
Wed Aug 26 2020
Journal Name
Iraqi Journal Of Agricultural Sciences
COMPARISON THE ACCURACY OF COMPUTING POINT COORDINATS BETWEEN DIFFERENT INSTRUMENTS AND APPLICATIONS OF GPS
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The study was aimed to determine the coordinates of  the points were measured by different ways and different instruments, the most precise way using the differential global positioning system (DGPS) that will be the reference measurements in comparison, less precise way using navigator GPS. Google earth (pro.), and the other applications of GPS mobile ( Samsung and I-phone). In this research (8 points) were chosen that are occasional in location. The comparison of the different observations can give us an idea of ​​the extent to which the accuracy of the observations differs from the different devices used in the observing, as well as through the knowledge of the best device and the best way to measure coordinates accurately t

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Study of different geostatistical methods to model formation porosity (Cast study of Zubair formation in Luhais oil field)
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Abstract<p>This study is concerned with making comparison in using different geostatistical methods for porosity distribution of upper shale member - Zubair formation in Luhais oil field which was chosen to study.</p><p>Kriging, Gaussian random function simulation and sequential Gaussian simulation geostatistical methods were adopted in this study. After preparing all needed data which are contour map, well heads of 12 wells, well tops and porosity from CPI log. Petrel software 2009 was used for porosity distribution of mentioned formation in methods that are showed above. Comparisons were made among these three methods in order to choose the best one, the comparing cri</p> ... Show More
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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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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 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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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Nelson-Olson Method and Two-Stage Limited Dependent Variables (2SLDV ) Method for the Estimation of a Simultaneous Equations System (Tobit Model)
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This study relates to  the estimation of  a simultaneous equations system for the Tobit model where the dependent variables  ( )  are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods  different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method  and  Two- Stage limited dependent variables(2SLDV) method  to get of estimators that hold characteristics the good estimator .

That is , parameters will be estim

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Data Analytics and Blockchain: A Review
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Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
Reducing Lost Circulation Problem by Using Rice Material
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Drilling fluid loss during drilling operation is undesirable, expensive and potentially hazardous problem.

    Nasiriyah oil field is one of the Iraqi oil field that suffer from lost circulation problem. It is known that Dammam, um-Radoma, Tayarat, Shiranish and Hartha are the detecting layers of loss circulation problem. Different type of loss circulation materials (LCMs) ranging from granular, flakes and fibrous were used previously to treat this problem.  

    This study presents the application of rice as a lost circulation material that used to mitigate and stop the loss problem when partial or total losses occurred.

     The experim

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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