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comparison Bennett's inequality and regression in determining the optimum sample size for estimating the Net Reclassification Index (NRI) using simulation

 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 data type and type of medical study. The probabilistic values obtained from the artificial neural network are used to calculate the net reclassification index (NRI).  A program was written for this purpose using the statistical programming language (R), where the mean maximum absolute error criterion (MME) of the net reclassification network index (NRI) was used to compare the methods of specifying the sample size and the presence of the number of different default parameters in light of the value of a specific error margin (ε). To verify the performance of the methods using the comparison criteria above were the most important conclusions were that the Bennett inequality method is the best in determining the optimum sample size according to the number of default parameters and the error margin value

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Publication Date
Tue Aug 18 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Forgotten Index and Forgotten Coindex of Graphs

F index is a connected graph, sum of the cubes of the vertex degrees. The forgotten topological index has been designed to be employed in the examination of drug molecular structures, which is extremely useful for pharmaceutical and medical experts in understanding the biological activities. Among all the topological indices, the forgotten index is based on degree connectivity on bonds. This paper characterized the forgotten index of union of graphs, join graphs, limits on trees and its complements, and accuracy is measured. Co-index values are analyzed for the various molecular structure of chemical compounds

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Publication Date
Sat Jan 01 2005
Journal Name
Journal Of The College Of Languages (jcl)
The Vogue of the Restoration Comedy of Manners and George Etherage's The Man of Mode; or, Sir Fopling Flutter

The Vogue of the Restoration Comedy of Manners and George Etherage's The Man of Mode; or, Sir Fopling Flutter

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Indirect Spectrofluorometric Method for the Determination of Cefotaxime Sodium, Ciprofloxacin Hydrochloride and Famotidine in Pharmaceuticals Using Bromate-Bromide and Acriflavine Dye

An Indirect simple sensitive and applicable spectrofluorometric method has been developed for the determination of Cefotaxime Sodium (CEF), ciprofloxacin Hydrochloride (CIP) and Famotidine (FAM) using reaction system bromate-bromide and acriflavine (AF) as fluorescent dye. The method is based on the oxidation of drugs with known excess bromate-bromide mixture in acidic medium and subsequent determination of unreacted oxidant by quenching fluorescence of AF. Fluorescence intensity of residual AF was measured at 528 nm after excitation at 402 nm. The fluorescence-concentration plots were rectilinear over the ranges 0.1-3.0, 0.05-2.6 and 0.1-3.8 µg ml-1 with lower detection limits of 0.013, 0.018 and 0.021 µg ml-1 an

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing the impact of exchange rate fluctuations and inflation on the GDP in Iraq using the modern methodology of Cointegration for the period (1988-2020)

     The research aims to analyze the impact of exchange rate fluctuations (EXM and EXN) and inflation (INF) on the gross domestic product (GDP) in Iraq for the period 1988-2020. The research is important by analyzing the magnitude of the macroeconomic and especially GDP effects of these variables, as well as the economic effects of exchange rates on economic activity. The results of the standard analysis using the ARDL model showed a long-term equilibrium relationship, according to the Bound Test methodology, from explanatory (independent) variables to the internal (dependent) variable, while the value of the error correction vector factor was negative and moral at a level less than (1%). The relationship bet

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Publication Date
Mon Jan 13 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Analyzing the net profitability of total investments using a constructed mathematical model: An applied research at Iraqi Middle East Bank for investment for the financial years 2008-2010

The trading banks in Iraq invest their funds according to regulations imposed by the Central Bank in Iraq in different financial fields like stock exchanges, acquire stocks as assets that could be sold at any time as well as make loans and contributing in corporations establishment also magnitude foreign capital through direct contacts with foreign exchange markets.

We can summarize the problem of this paper as shortage in mathematical models that used in studying and analyzing these investments and according to this problem we used (a constructed mathematical model ) consists of three major indicators: profitability of total investment assets which is divided into three sub-indicators: owners equity risk indicator, debits risk i

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Publication Date
Sat Oct 02 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors

Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

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Publication Date
Sun Jan 01 2017
Journal Name
Research Journal Of Pharmacy And Technology
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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness

Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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