<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

Objective(s): The aim of the study was to identify the prevalence of overweight and obesity in adolescence and
to estimate the effect of socio- demographic and health behaviors that predicting obesity in adolescents.
Methodology: A cross-sectional descriptive study was being carried out at three public Arabic secondary
schools in Erbil city from October 1
st 2010 to January 30th 2011. A systematic randomly sample size of 461 students
was selected.
Results: In this study, the age of (46.2%, 122) of males students were ranged between (17- 18.9) years old compared
to females students (74.1%, 146) their age ranged between (15 -16.9) years old. About (3.4%, 9) of males
adolescents having overweight while all female ado

152 sera were collected from healthy individuals residing A;-Haweja City were tested for antibody titers for brucella antigens by slide agglutination test

The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through  finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy

A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Most of the mosques in the Islamic world fall under specific and known forms and patterns to a large extent, and such patterns have grown and evolved from the few basic and uniform models, but they changed slowly due to the impact with a mixture of changing functional requirements and cultural landscapes because of the variables of time and place to form patterns known and famous in this day across parts of the Islamic world and its borders. There was no exception to these patterns, but small numbers of mosques that were probably the result of personal experiences or improvisational resolutions, or in response to specific or temporary stimuli. However, the emergence of a specific pattern which does not belong to any of these patt

SH Mahdi, AM Mahdi, KS Ismaeil, College of Education for Pure Science, Ibn-Al-Haitham, 2015 - Cited by 7