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 dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

Background: In healthcare settings, specialists from different fields may follow the most well-known, reliable, and easy-to-understand medical guidelines. This study aimed to determine Iraqi physicians' adherence to treatment guidelines, to specify which treatment guidelines are utilized for each disease and identify their barriers to follow the guidelines.

Methods: This was qualitative study including face-to-face and virtual semi-structured interviews with specialist physicians from different disciplines. The interviews were conducted between December 2021 and May 2022 in Kirkuk province, Iraq. The qualitative data generated through i

The productivity of oil wells may be improved by determining the value of enhancing well productivity and the likely reasons or sources of formation damage after the well has been recognized as underperforming. Oil well productivity may be improved, but the economics of this gradual improvement may be compromised. It is important to analyze the influence of the skin effect on the recovery of the reserve.    The acid treatment evaluated for the well AD-12, primarily for the zone Mi4;  using a license of Stimpro Stimulation Software to validate the experimental work to the field scale, this software is considered the most comprehensive instrument for planning and monitoring matrix acid treatments and utilizing actual data to provide a far

The productivity of oil wells may be improved by determining the value of enhancing well productivity and the likely reasons or sources of formation damage after the well has been recognized as underperforming. Oil well productivity may be improved, but the economics of this gradual improvement may be compromised. It is important to analyze the influence of the skin effect on the recovery of the reserve.

   The acid treatment evaluated for the well AD-12, primarily for the zone Mi4;  using a license of Stimpro Stimulation Software to validate the experimental work to the field scale, this software is considered the most comprehensive instrument for planning and monitoring matrix acid treatments and utilizing actual data to prov