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Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in R program by using some existing packages.</p>
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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Use aggregate slide estimate additive splines estimation for the diagnosis of non-linear composite model self-regression with practical application
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Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Comparison of Estimate Methods of Multiple Linear Regression Model with Auto-Correlated Errors when the Error Distributed with General Logistic
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Comparison of Estimate Methods of Multiple Linear Regression Model with Auto-Correlated Errors when the Error Distributed with General Logistic
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

Publication Date
Sun May 07 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Elastic Behavior of Lead Germanate Near Transition Temperature
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All the stiffened and unstiffened elastic constants for lead germanate (Pb5Ge3O11) single
crystal have been measured from room temperature 298 K up to 513K by using ultrasonic
pulse superposition technique. The correction of piezoelectric stiffening has been used to
obtain the unstiffened elastic constants. Elastic moduli of lead germanate (C11, C33, C12, C13,
C44 and C66) decrease with the increase of temperature. C11, C33, C
12 and C13 suffered a dip at
transition temperature but they increase with the increase of temperature just above Curie
temperature between 453 and 473 K because of their positive temperature coefficients in this
range, and then decrease slightly (except C12 increases) in the

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Elastic longitudinal electon catterting B from factors of
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Electronic Alattarh been studied long flexible factors forming the nucleus of boron in the shell model framework multipolar been identified factors was introduced into the effects of polarization heart in the first place accounts

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Elastic Form Factors and Matter Density Distributions of Some Neutron-Rich Nuclei
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The ground-state properties of exotic 18N and 20F nuclei, including the neutron, proton and matter densities and related  radii are investigated using the two-body model of   within Gaussian (GS) and Woods Saxon (WS) wave functions. The long tail is evident in the computed neutron and matter densities of these nuclei. The plane wave Born approximation (PWBA) is  calculate the elastic form factors of these exotic nuclei. The variation in the proton density distributions due to the presence of the extra neutrons in 18N and 20F leads to a major difference between the elastic form factors of these exotic nuclei and their stable isotopes 14N and 19F. The reaction c

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Publication Date
Sun Apr 29 2018
Journal Name
Iraqi Journal Of Science
Modified Artificial immune system as Feature Selection
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Feature selection algorithms play a big role in machine learning applications. There are several feature selection strategies based on metaheuristic algorithms. In this paper a feature selection strategy based on Modified Artificial Immune System (MAIS) has been proposed. The proposed algorithm exploits the advantages of Artificial Immune System AIS to increase the performance and randomization of features. The experimental results based on NSL-KDD dataset, have showed increasing in performance of accuracy compared with other feature selection algorithms (best first search, correlation and information gain).

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Publication Date
Tue May 10 2022
Journal Name
European Scholar Journal (esj)
MODELING AND COMPARISON OF CLOSED-LOOP AND OPENLOOP ADAPTIVE OPTICS SYSTEMS
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Astronomers have known since the invention of the telescope that atmospheric turbulence affects celestial images. So, in order to compensate for the atmospheric aberrations of the observed wavefront, an Adaptive Optics (AO) system has been introduced. The AO can be arranged into two systems: closedloop and open-loop systems. The aim of this paper is to model and compare the performance of both AO loop systems by using one of the most recent Adaptive Optics simulation tools, the Objected-Oriented Matlab Adaptive Optics (OOMAO). Then assess the performance of closed and open loop systems by their capabilities to compensate for wavefront aberrations and improve image quality, also their effect by the observed optical bands (near-infrared band

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Publication Date
Mon May 14 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Accurate MHD Flux Solutions of a Viscose Fluid and Generalized Burgers' Model fluxwithin an Annular Pipe Under Sinusoidal Pressure
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The aim of this work presents the analytical studies of both the magnetohydrodynamic (MHD) flux and flow of the non-magnetohydro dynamic (MHD) for a fluid of generalized Burgers’ (GB) withinan annular pipe submitted under Sinusoidal  Pressure (SP)gradient. Closed beginning velocity's' solutions are taken by performing the finite Hankel transform (FHT) and Laplace transform (LT) of the successivefraction derivatives. Lastly, the figures were planned to exhibition the transformations effects of different fractional parameters (DFP) on the profile of velocity of both flows.

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Publication Date
Fri Jul 01 2022
Journal Name
Iraqi Journal Of Science
The Effect of Expected Water Shortage on Net Primary Productivity and Rain Use Efficiency in the Tigris-Euphrates Basin
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Tigris and Euphrates Rivers, originating in Turkey and cutting through both Syria and Iraq, have experienced drastic reductions in water flows in recent years due to increasing water demand, hydro-engineering projects, and climate change. The decline in water flows has led to decreased agricultural yields. Iraq reported its worst cereal harvest in a decade in 2009, indicating that with a decline in water supplies, a potential food security problem emerges. This study, therefore, addressed the effect of water availability on (1) Net Primary Productivity (NPP) and (2) Rain Use Efficiency (RUE) in the Tigris-Euphrates (T-E) basin. Results displayed that NPP increases significantly from the arid and semi-arid sites in the south to the wetter

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