In this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process,  where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliab

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

Breast cancer (BC) is the most prevalent tract cancer in the world, including Iraq. The classified breast tumors to benign, malignant, and radiotherapy. Cancer treatment depends on certain stages such as mastectomy then chemotherapy alone or with radiation therapy or endocrine therapy according to the prognostic features obtained from the pathology report. The present study included 100 females. The women were split into two groups, control group that consisted of 50 apparently healthy females and 50 patients with BC group who undergo the radiotherapy. The current study highlighted on some of the anthropometric measurements, including the oxidative stress index malondialdehyde (MDA), the concentrations of total antioxidant capacity (TAC), s

Breast cancer (BC) is the most prevalent tract cancer in the world, including Iraq. The classified breast tumors to benign, malignant, and radiotherapy. Cancer treatment depends on certain stages such as mastectomy then chemotherapy alone or with radiation therapy or endocrine therapy according to the prognostic features obtained from the pathology report. The present study included 100 females. The women were split into two groups, control group that consisted of 50 apparently healthy females and 50 patients with BC group who undergo the radiotherapy. The current study highlighted on some of the anthropometric measurements, including the oxidative stress index malondialdehyde (MDA), the concentrations of total antioxidant capacity (TAC), s

To investigate the activity and role of certain enzyme markers in 30 patients female with breast cancer (non-treated, treated, and treatment with recovered).The serum activity of enzyme tumor markers (ALP, GPT and GOT) of (30) patients with breast cancer, and (7) healthy control subjects by using statistical analysis: There is significant difference higher in activity of serum enzyme tumor markers (ALP, GPT, and GOT) in all patients as compared with healthy control

                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

Due to the lack of statistical researches in studying with existing (p) of Exogenous Input variables, and there contributed in time series phenomenon as a cause, yielding (q) of Output variables as a result in time series field, to form conceptual idea similar to the Classical Linear Regression that studies the relationship between dependent variable with explanatory variables. So highlight the importance of providing such research to a full analysis of this kind of phenomena important in consumer price inflation in Iraq. Were taken several variables influence and with a direct connection to the phenomenon and analyzed after treating the problem of outliers existence in the observations by (EM) approach, and expand the sample size (n=36) to

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the