In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T

Background: Placenta is a chief cause of maternal and perinatal mortality and significant factor in fetal growth retardation. It undergoes different variations in weight, volume, structure, shape and function continuously throughout the gestation tosupport the prenatal life. Cautious examination of placenta can give information which can be useful in the management of complications in mother and the newborn. Objective: The present work has been attempted towards determination of the morphological ( macroscopic and microscopic) parameters of human full-term placentae and their relation with different parity and age group of mothers. Patients and Methods: A whole of 40 placentae were recently collected.They were divided into four groups

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

Background: Soft Laser has been advantageous in medical applications and is widely used in clinical practice. It is applied because it doesn’t cause the significant thermal effects or tissue hurt when irradiated. The blood response to low power laser radiation provides information about processes of laser radiation interaction with live creatures. Objective: The aim of the current work was to evaluate the laser-induced changes of in vitro erythrocyte sedimentation rate (ESR), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC) in patients with breast cancer by irradiating a human blood sample using a green laser and comparing its effects before and after irradiation with the same power density (100mW/c

   The technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.

 There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

This work studies with produce of light fuel fractions of gasoline, kerosene and gas oil from treatment of residual matter that will be obtained from the solvent extraction process as by product from refined lubricate to improve oil viscosity index in any petroleum refinery. The percentage of this byproduct is approximately 10% according to all feed (crude oil) in the petroleum refinery process. The objective of this research is to study the effect of the residence time parameter on the thermal cracking process of the byproduct feed at a constant temperature, (400 °C). The first step of this treatment is the thermal cracking of this byproduct material by a constructed batch reactor occupied with control device at a selective range of re