Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

  Anthropogenic activities cause soil pollution with different serious pollutants, such as polycyclic aromatic hydrocarbon (PAHs) compounds. This study assessed the contamination of PAHs in soil samples collected from 30 sites divided into eight groups (residential areas, oil areas, agricultural areas, roads, petrol stations, power plants, public parks and electrical generators) in Basrah city-Iraq during 2019-2020. The soil characteristics including (moisture, pH, EC and TOC) were measured. Results showed the following ranges (soil moisture (0.03-0.18%),pH (6.90-8.16), EC (2.48-104.80) mS/cm and TOC (9.90-20.50%)). Gas Chromatography (GC) was used to measure PAHs in extracted soil samples. The total PAH range (499.96 - 5864.86) ng/g dr

Uropathogenic specific protein is a genotoxic protein targeting the DNA, leading to mutations and modifications in the normal cell's DNA and subsequently, cancer development. This study aims to determine the prevalence of the usp gene in Uropathogenic Escherichia coli isolated from females with urinary tract infections and study its correlation with biofilm formation. One hundred and five urine specimens were collected from female patients (20 to 55 years old) with urinary tract infections attending hospitals. Traditional laboratory methods using selective and differential culture media were used for initial bacterial isolation and identification, and molecular techniques that targeted a segment of the 16SrRNA gene with a specific primer pa

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.