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bsj-5159
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage and Selection Operator (Lasso), and Tikhonov Regularization (Ridge). The simulation studiesshow that the performance of our method is better than the othersaccording to the error and the time complexity. Thesemethodsare applied to a real dataset, which is called Rock StrengthDataset.The new approach implemented using the Gibbs sampler is more powerful and effective than other approaches.All the statistical computations conducted for this paper are done using R version 4.0.3 on a single processor computer.

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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Using Benford’s law to detecting earnings management Application on a sample of listed companies in the Iraqi market for securities
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Abstract

The net profit reported in the annual financial statements of the companies listed in the financial markets, is considered one of the Sources of information relied upon by users of accounting information in making their investment decisions. At the same time be relied upon in calculating the bonus (Incentives) granted to management, therefore the management of companies to manipulate those numbers in order to increase those bonuses associated to earnings, This practices are called earnings management practices. the manipulation in the figures of earnings by management will mislead the users  of financial statements who depend on reported earnings in their deci

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Publication Date
Tue Mar 08 2022
Journal Name
Multimedia Tools And Applications
Comparison study on the performance of the multi classifiers with hybrid optimal features selection method for medical data diagnosis
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Publication Date
Wed Mar 01 2017
Journal Name
Diyala Journal Of Engineering Sciences
NFLUENCE OF WATER SOURCE ON COMPRESSIVE STRENGTH OF HIGH STRENGTH CONCRETE
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This research studies the influence of water source on the compressive strength of high strength concrete. Four types of water source were adopted in both mixing and curing process these are river, tap, well and drainage water (all from Iraq-Diyala governorate). Chemical analysis was carried out for all types of the used water including (pH, total dissolved solids (TDS), Turbidity, chloride, total suspended solid (TSS), and sulfates). Depending on the chemical analysis results, it was found that for all adopted sources the chemical compositions was within the ASTM C 1602/C 1602M-04 limits and can be satisfactorily used in concrete mixtures. Mixture of high strength concrete for compressive strength of (60 MPa) was designed and checked using

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Robust Optimization with practical application
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The purpose of this paper is applying the robustness in Linear programming(LP) to get rid of uncertainty problem in constraint parameters, and find the robust optimal solution, to maximize the profits of the general productive company of vegetable oils for the year 2019, through the modify on a mathematical model of linear programming when some parameters of the model have uncertain values, and being processed it using robust counterpart of linear programming to get robust results from the random changes that happen in uncertain values ​​of the problem, assuming these values belong to the uncertainty set and selecting the values that cause the worst results and to depend buil

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Publication Date
Thu Sep 20 2007
Journal Name
Journal Of Physical Education
The effect of high-intensity interval training (using weights) during the special preparation period on functional variables among junior basketball players
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This study is concerned with the comparison of the results of some tests of passing and dribbling of the basketball of tow different years between teams of chosen young players in Baghdad. Calculative methods were used namely (Arithmetic mean, Value digression and T.test for incompatible specimens). After careful calculative treatments, it has been that there were abstract or no abstract differences in the find results of chestpass, highdribble and cross-over dribble. The clubs were: (Al-Khark, Air defence, Police and Al-Adamiyah) each one separate from the other for the year (2000-2001). After all that many findings were reached such as the lack of objective valuation (periodical tests) between one sport season and the other. In the light

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Publication Date
Wed Apr 30 2025
Journal Name
Iraqi Journal Of Science
Calculating the Variation of the Universal Parameter (Variable) Using Kepler's Equation for Different Orbits
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Stumpff functions are an infinite series that depends on the value of z. This value results from multiplying the reciprocal semi-major axis with a universal anomaly. The purpose from those functions is to calculate the variation of the universal parameter (variable) using Kepler's equation for different orbits. In this paper, each range for the reciprocal of the semi-major axis, universal anomaly, and z is calculated in order to study the behavior of Stumpff functions C(z) and S(z). The results showed that when z grew, Stumpff functions for hyperbola, parabola, and elliptical orbits were also growing. They intersected and had a tendency towards zero for both hyperbola and parabola orbits, but for elliptical orbits, Stumpff functions

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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Compensation of the Nonlinear Power Amplifier by Using SCPWL Predistorter with Genetic Algorithm in OFDM technique
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The High Power Amplifiers (HPAs), which are used in wireless communication, are distinctly characterized by nonlinear properties. The linearity of the HPA can be accomplished by retreating an HPA to put it in a linear region on account of power performance loss. Meanwhile the Orthogonal Frequency Division Multiplex signal is very rough. Therefore, it will be required a large undo to the linear action area that leads to a vital loss in power efficiency. Thereby, back-off is not a positive solution. A Simplicial Canonical Piecewise-Linear (SCPWL) model based digital predistorters are widely employed to compensating the nonlinear distortion that introduced by a HPA component in OFDM technology. In this paper, the genetic al

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of parameters of two-dimensional sinusoidal signal model by employing Deferential Evaluation algorithm and the use of Sequential approach in estimation
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Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

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Publication Date
Fri Jan 01 2010
Journal Name
Iraqi Journal Of Science
RETRIEVING DOCUMENT WITH COMPACT GENETIC ALGORITHM(CGA)
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