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).

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

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

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

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.

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

The goal of the current study was to research the changes in hematological parameters: WBC count, RBCs count, Hb, PCV, neutrophil, lymphocyte, and monocyte in albino mice infected with Aspergillus fumigatus by intraperitoneal injection after induced immunosuppression by intraperitoneal injection of cortisone. The current research also examined an attempt to reduce the infection load by treating Solanum aculeastrum. The result shows higher decreased significance (P≤0. 05) in RBCs, Hb, and PCV after being infected with A. fumigatus 7. 1 ± 0. 8, 11. 3 ± 0. 5 and 41. 5 ± 2. 4, respectively, while the total WBC count, neutrophil, lymphocyte, and monocytes were increased significantly (P≤0. 05) after treatment with S. aculeastrum i

The present research  investigates joints welding of 304L austenitic stainless steel using metal inert gas (MIG) welding method. The research explores the effect of process parameters (arc voltage, wire feed rate, and electrode wire diameter) on the mechanical properties of stainless steel.  The above variables are varied  respectively with 18.5, 19, 19.5 V, 116, 127, 137 mm/s, and 0.8, 1, 1.2 mm, with E308L as a filler electrode. The design matrix of the experiments was determined using the design of experiment (DOE) program Minitab 17 based on the levels of input elements used. The Taguchi orthogonal matrix methodology (Taguchi) technique was used to develop some empirical analysis for the maximum tensile strength and proper surface