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 Distanc

The aim of this paper is to present a method for solving high order ordinary differential equations with two point's boundary condition, we propose semi-analytic technique using two-point oscillatory interpolation to construct polynomial solution. The original problem is concerned using two-point oscillatory interpolation with the fit equal numbers of derivatives at the end points of an interval [0 , 1] . Also, many examples are presented to demonstrate the applicability, accuracy and efficiency of the method by comparing with conventional methods.

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

Radioactive elements were identified in samples of imported coffee consumed in the province of Basra using gamma spectrometry SAM940TM. It is a scintillation detector of NaI(Tl) crystal and the dimensions of 2×2 inch. We have identified specific concentration As(Bq/kg) and annual effective dose D(Sv/y) for radioactive elements (_^40)K, (_^131)I, (_^134)Cs and (_^137)Cs. The estimated average effective dose for adults from coffee samples were found to be 0.037mSv/y, 88.434nSv/y, 46.909nSv/y, 27.212nSv/y for ((_^40)K,(_^131)I,(_^134)Cs,(_^137)Cs) respectively. The present results of the study revealed that the radioactivity was relatively low in the coffee and within the permissiblelimit.

Abstract

            Rayleigh distribution is one of the important distributions used for analysis life time data, and has applications in reliability study and physical interpretations. This paper introduces four different methods to estimate the scale parameter, and also estimate reliability function; these methods are Maximum Likelihood, and Bayes and Modified Bayes, and Minimax estimator under squared error loss function, for the scale and reliability function of the generalized Rayleigh distribution are obtained. The comparison is done through simulation procedure, t

Objectives: This study aimed to identify and study most properties of the specific and general health-related
quality-of-life (HRQoL) in prostate cancer patients, as well as creating a new measurement scale for assessing QoL
among prostate cancer patients.
Methodology: A cross sectional (descriptive) study was conducted to evaluate General Quality of life in patients
with prostate cancer. A sample of 100 prostate cancer patients from Al-Amal National hospital for cancer
management and Oncology Center in Baghdad Medical City. This study applied format of General World Health
Organization Quality of Life-BERF questionnaire. The methods used descriptive statistics to evaluate the General
QoL-Improvements, as well as inf

The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.