This paper uses classical and shrinkage estimators to estimate the system reliability (R) in the stress-strength model when the stress and strength follow the Inverse Chen distribution (ICD). The comparisons of the proposed estimators have been presented using a simulation that depends on the mean squared error (MSE) criteria.

The estimation of the stressÙ€ strength reliability of Invers Kumaraswamy distribution will be introduced in this paper based on the maximum likelihood, moment and shrinkage methods. The mean squared error has been used to compare among proposed estimators. Also a Monte Carlo simulation study is conducted to investigate the performance of the proposed methods in this paper.

This paper deals with defining Burr-XII, and how to obtain its p.d.f., and CDF, since this distribution is one of failure distribution which is compound distribution from two failure models which are Gamma model and weibull model. Some equipment may have many important parts and the probability distributions representing which may be of different types, so found that Burr by its different compound formulas is the best model to be studied, and estimated its parameter to compute the mean time to failure rate. Here Burr-XII rather than other models is consider  because it is used to model a wide variety of phenomena including crop prices, household income, option market price distributions, risk and travel time. It has two shape-parame

The aim of this study is to extract and utilise the bark of Berlinia grandiflora as a natural dye source for the colouration of cotton and polyamide 6 fabrics. The solvents used for this study were water, methanol, acetone, and methanol/potassium hydroxide. The best of all the solvents used was water. In the extraction process, the various solvents were extracted with Soxhlet extractor.  The optimum colourant extraction was observed at 40 °C for 2 h.  The extracted compound was isolated and characterized by UV spectrophotometry; proton and carbon-13 nuclear magnetic resonance, mass spectrometry, and Fourier transform infrared spectroscopy.  Mordanting and subsequent dyeing of cotton and polyamide 6 fabrics with t

Pera Magroon anticline is located within the northeastern of Iraq, covering area estimated by 958 Km². The Landsat ETM⁺ false color composite imagery was produced by assigning [741] bands. It is used to distinguish alluvial fans in the southwestern limb of Pera Magroon anticline. Digital elevation models (DEM) were used for describing topographic features related to the alluvial fans, as well as, three dominations model (3D) was created from (DEM) and the Landsat ETM⁺ image.

 Arc GIS, hydro tool set was used to draw the drainage patterns, the area of study was covered by dendritic and parallel patterns. Contour lines across the fans form segments of ellipses reveal the pattern of tectonic act

Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F