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Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very good startup to establish a rule of thumb in the laboratories to compare between observations. The importance of linear regression equations in predicting surface water quality parameters is a method that can be applied to any other location.

 

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Civilizations and Environmental Particulars of Place in Islamic Holy Thresholds in Iraq (Alkadhumain Holy Threshold as a case study)
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Islamic shrines architecture is one of the Islamic Architectural building types. It is called (Thresholds); (Atabat) in Arabic. Thoroughbred throughout the Islamic world from the east to west. In addition, it carries the style features and peculiarities of uniqueness from the rest of the types of Islamic architecture. By virtue of the particularity of its function as tomb for important person in Islamic history. Islamic shrines architecture has grown and evolved in started from the small shrines, and then taken to widen with the evolution of time in line with the value of the event and the rituals associated with it. Some of them to became centers of large cities of the largest in many parts of the Islamic world.

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Wildlife Diseases
MENINGEAL WORM (PARELAPHOSTRONGYLUS TENUIS) AS A CAUSE OF MORTALITY IN THE RESTORED ELK (CERVUS CANADENSIS) POPULATION IN MISSOURI, USA
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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
comparison Bennett's inequality and regression in determining the optimum sample size for estimating the Net Reclassification Index (NRI) using simulation
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 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Pakistan Association Of Dermatologists
Zinc as an essential element for normal immune reactions and as a therapeutic agent for autoimmune diseases
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Publication Date
Sun Oct 18 2026
Journal Name
Al-rafidain University College For Sciences
“Simple Regression Analysis by using Linear Programming Technique and illustration of Absolute Residuals method with another Estimation Techniques”
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This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Stator Faults Diagnosis and Protection in 3-Phase Induction Motor Based on Wavelet Theory
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Performance evaluation criteria"Applied Study in the General Company for the manufacture of glass and ceramics"
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Contemporary management is interested in the process of performance assessment  because of its significance in the field of planning and controlling the multiactiveties to attain its goals and uncovering digression of virtual performance after comparing it with the plan or equitable performance.

Digression is analyzed to enable management control centers of authority.

Assessment process significance is closely related by setting definite categories to evaluate the economic activity to know the ability to achieves aims.

This study concentrated on the most important categories that used to evaluate  company understudy with ather categories suggested to complete assessment process.

This study is in

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