The current work is characterized by simplicity, accuracy and high sensitivity Dispersive liquid - Liquid Micro Extraction (DLLME). The method was developed to determine Telmesartan (TEL) and Irbesartan (IRB) in the standard and pharmaceutical composition. Telmesartan and Irbesartan are separated prior to treatment with Eriochrom black T as a reagent and formation ion pair reaction dye. The analytical results of DLLME method for linearity range (0.2- 6.0) mg /L for both drugs, molar absorptivity were (1.67 × 105-    5.6 × 105) L/ mole. cm, limit of detection were (0.0242and0.0238), Limit of quantification were (0.0821and0.0711), the Distribution coefficient were

Inferential methods of statistical distributions have reached a high level of interest in recent years. However, in real life, data can follow more than one distribution, and then mixture models must be fitted to such data. One of which is a finite mixture of Rayleigh distribution that is widely used in modelling lifetime data in many fields, such as medicine, agriculture and engineering. In this paper, we proposed a new Bayesian frameworks by assuming conjugate priors for the square of the component parameters. We used this prior distribution in the classical Bayesian, Metropolis-hasting (MH) and Gibbs sampler methods. The performance of these techniques were assessed by conducting data which was generated from two and three-component mixt

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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

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

Conservative pipes conveying fluid such as pinned-pinned (p-p), clamped–pinned (c-p) pipes and clamped-clamped (c-c) lose their stability by buckling at certain critical fluid velocities. In order to experimentally evaluate these velocities, high flow-rate pumps that demand complicated fluid circuits must be used.

     This paper studies a new experimental approach based on estimating the critical velocities from the measurement of several fundamental natural frequencies .In this approach low flow-rate pumps and simple fluid circuit can be used.

Experiments were carried out on two pipe models at three different boundary conditions. The results showed that the present approach is more accurate for est

Nitroso-R-salt is proposed as a sensitive spectrophotometric reagent for the determination of paracetamol in aqueous solution. The method is based on the reaction of paracetamol with iron(III) and subsequent reaction with nitroso-R-salt to yield a green colored complex with maximum absorption at 720 nm. Optimization of the experimental conditions was described. The calibration graph was linear in the concentration range of 0.1 – 2.0 ?g mL-1 paracetamol with a molar absorptivity of 6.9 × 104 L mol-1 cm-1. The method was successfully applied to the determination of paracetamol in pharmaceutical preparations without any interference from common excipients. The method has been statistically evaluated with British Pharmacopoeia method a