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 mixture of the Rayleigh distribution according to several scenarios and comparing the results of the scenarios by calculating the mean of classification successful rate (MCSR) and the mean of mean square error(MMSE). The results showed that Gibbs sampler algorithm yields a better computation results than the others in terms of MMSE and MCSR.
Real Time Extended (RTX) technology works to take advantage of real-time data comes from the global network of tracking stations together with inventor locating and compression algorithms to calculate and relaying the orbit of satellite, satellite atomic clock, and any other systems corrections to the receivers, which lead to real-time correction with high accuracy. These corrections will be transferred to the receiver antenna by satellite (where coverage is available) and by IP (Internet Protocol) for the rest of world to provide the accurate location on the screen of smartphone or tablet by using specific software. The purpose of this study was to assess the accuracy of Global Navig
The current study was designed to investigate the alterations in the ultrastructure of orgenelles and cellular activity of exocrine pancreatic acini of experimentally induced-diabetic rats and to assess the usefulness of herbal combination supplementation in improving the ultrastructure and cellular activity of exocrine pancreas. The number of albino male rats used were 24 which divided into equally 4 groups; group I: control group, group II: alloxan-induced diabetes mellitus (single intraperitoneal dose of alloxan 120 mg/kg for 3 days), group III: herbal combination treatment composed from the extracts of fenugreek seeds (Trigonella foenum-graecum), black cumin (Nigella sativa) seeds, rhizomes
... Show MoreIn this research a local adsorbent was prepared from waste tires using two-step pyrolysis method. In the carbonization process, nitrogen gas flow rate was 0.2L/min at carbonization temperature of 500ºC for 1h. The char products were then preceded to the activation process at 850°C under carbon dioxide (CO2) activation flow rate of 0.6L/min for 3h. The activation method produced local adsorbent material with a surface area and total pore volume as high as 118.59m2 /g and 0.1467cm3/g, respectively. The produced . local adsorbent (activated carbon) was used for adsorption of lead from aqueous solution. The continuous fixed bed column experiments were conducted. The adsorption capacity performance of prepared activated carbons in this work
... Show MorePoverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc
... Show MoreThis study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators