In this article, it is interesting to estimate and derive the three parameters which contain two scales parameters and one shape parameter of a new mixture distribution for the singly type one censored data which is the branch of right censored sample. Then to define some special mathematical and statistical properties for this new mixture distribution which is considered one of the continuous distributions characterized by its flexibility. Next,  using maximum likelihood estimator method for singly type one censored data based on the Newton-Raphson matrix procedure to find and estimate values of these three parameter by utilizing the real data taken from the National Center for Research and Treatment of Hematology/University of Mus

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

The permeable reactive barrier (PRB) is one of the promising innovative in situ groundwater remediation technologies, in removing of copper from a contaminated shallow aquifer. The 1:1- mixture of waste foundry sand (WFS) and Kerbala’s sand (KS) was used for PRB. The WFS was represented the reactivity material while KS used to increase the permeability of PRB only. However, Fourier-transform infrared (FTIR) analysis proved that the carboxylic and alkyl halides groups are responsible for the sorption of copper onto WFS. Batch tests have been performed to characterize the equilibrium sorption properties of the (WFS+KS) mix in copper- containing aqueous
solutions. The sorption data for Cu+2 ions, obtained by batch experiments, have be

Measurements of radon gas concentrations were carried out for 12 soil samples at 3 sampling depths (surface, 5 cm and 10 cm) collected from (4) locations in south Baghdad suburbs (Bu'aitha) using solid state nuclear track detector CR-39 and sealed can technique. Radon concentrations for surface samples were ranged from 402.2 to 1538.4 Bq.m^-3 with an average 994.4 Bq.m^-3. Whereas, radon concentration was ranged from 813.1to 2050.4 Bq.m^-3 and from 1309.8 to 4626. 1Bq.m^-3 with an average values of 1359.8 Bq.m^-3 and 2338.3 Bq.m^-3 for 5 cm and 10 cm depths respectively. Maximum radon level was found at the location near to the river (site S4) while the minimum radon level was f

Recently The problem of desertification and vegetation cover degradation become an environmental global challenge. This problem could be summarized as as the land cover changes. In this paper, the area of Al- Muthana in the south of Iraq will be consider as one of Semi-arid lands. For this purpose, the Ladsat-8 images can be used with 15 m in spatial resolution. In order to over Achieve the work, many important ground truth data must be collected such as, rain precipitation, temperature distribution over the seasons, the DEM of the region, and the soil texture characteristics. The extracted data from this project are tables, 2-D figures, and GIS maps represent the distributions of vegetation areas, evaporation / precipitation, river levels

This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro