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Analyzing big data sets by using different panelized regression methods with application: Surveys of multidimensional poverty in Iraq
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Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distance (ED) was used to compare the two methods and the research conclude that the SICA method is better than Ridge estimator with Big Data conditions.

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Publication Date
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Optimal Prediction Using Artificial Intelligence Application
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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of monetary policy variables inflation in Algeria: standard study using self regression time gaps
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                In the past years, the Algerian Economy has witnessed various monetary developments characterized by different monetary and banking reforms aimed by monetary authorities to achieve monetary stability and driving overall growth. It should be noted that there is evidence to initiate fundamental changes on the basis of which new monetary, financing and banking policy mechanisms must be formulated in Algeria by enhancing the pursuit of reforming the monetary system, in order to improve monetary and economic indicators.

                The study a

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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
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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 Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayesian methods to estimate the failure probability for electronic systems in case the life time data are not available
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In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Computer Science Trends And Technology
Secure Video Data Deduplication in the Cloud Storage Using Compressive Sensing
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Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

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Publication Date
Fri Jul 01 2022
Journal Name
Biomedicine And Chemical Sciences
Identification of Pathogenic Fungi in Renal Transplant Patients by Conventional and Molecular Methods
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Opportunistic fungal infections due to the immune- compromised status of renal transplant patients are related to high rates of morbidity and mortality regardless of their minor incidence. Delayed in identification of invasive fungal infections (IFIs), will lead to delayed treatment and results in high mortality in those populations. The study aimed to assess the frequency of invasive fungal infection in kidney transplant recipients by conventional and molecular methods. This study included 100 kidney transplant recipients (KTR) (75 males, and 25 females), collected from the Centre of Kidney Diseases and Transplantation in the Medical City of Baghdad. Blood samples were collected during the period from June 2018 to April 2019. Twent

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Use Simulation To Differentiate Between Some Modern Methods To the Model GM(1,1) To Find Missing Values And Estimate Parameters With A Practical Application
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Abstract

       The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and analyzing the demand function for agricultural imports in Iraq for the period (1980-2012) in Autoregressive Distributed Lag Model(ARDL)
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Abstract:

The issues related to foreign trade is a broad field for discussions and captures the interest of economists for their contribution to the process of economic development in the economies of the countries, especially developing ones. The imports of goods and services in foreign trade constitute an important part of the local by which the economy gets goods and services that the economy cannot produce because of the incompetent base of production. Further, the demand function of imports occupied a good deal of the attention of researchers in the field of international economics for which agricultural imports constitute an important part. The reason for the interest in the subject is due to its im

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Publication Date
Mon Apr 20 2026
Journal Name
Applied Physics A
The antibacterial property of ZnO nanopowder with different concentration of sodium hydroxide prepared by hydrothermal method
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Publication Date
Sat Nov 28 2020
Journal Name
The Iraqi Journal Of Science
Removal of Aniline Blue from Textile Wastewater using Electrocoagulation with the Application of the Response Surface Approach
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This paper investigated the treatment of textile wastewater polluted with aniline blue (AB) by electrocoagulation process using stainless steel mesh electrodes with a horizontal arrangement. The experimental design involved the application of the response surface methodology (RSM) to find the mathematical model, by adjusting the current density (4-20 mA/cm2), distance between electrodes (0.5-3 cm), salt concentration (50-600 mg/l), initial dye concentration (50-250 mg/l), pH value (2-12 ) and experimental time (5-20 min). The results showed that time is the most important parameter affecting the performance of the electrocoagulation system. Maximum removal efficiency (96 %) was obtained at a current density of 20 mA/cm2, distance be

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