Uropathogenic Escherichia coli is the main cause of urinary tract infections, the ability of this bacteria to cause urinary tract infections is related to a variety of virulence factors that enhance colonization and evade the immune response, one of these virulence factors is cytotoxic necrotizing factor 1 toxin which converts the glutamine residue to glutamic acid to activated GTPase Rho family. The study was meant to find out the prevalence rate of the cnf1 gene in Uropathogenic Escherichia coli isolated from Iraqi patients. Conventional laboratory methods were used for primary bacterial identification and molecular methods were used to confirm bacterial identity and gene detection. Escherichia coli was identified in 89/165 (53.93%) of th

In this research we been estimated the survival function for data suffer from the disturbances and confusion of Iraq Household Socio-Economic Survey: IHSES II 2012 , to data from a five-year age groups follow the distribution of the Generalized Gamma: GG. It had been used two methods for the purposes of estimating and fitting which is the way the Principle of Maximizing Entropy: POME, and method of booting to nonparametric smoothing function for Kernel, to overcome the mathematical problems plaguing integrals contained in this distribution in particular of the integration of the incomplete gamma function, along with the use of traditional way in which is the Maximum Likelihood: ML. Where the comparison on the basis of the method of the Cen

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through  finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy

A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

CuInSe2(CIS) thin films have been prepared by use vacuum thermal evaporation technique, of thickness750 nm with rate of deposition 1.8±0.1 nm/sec on glass substrate at room temperature and pressure (10-5) mbar. Heat treatment has been carried out in the range (400-600) K for all samples. The optical properties of the CIS thin films are been studied such as (absorption coefficient, refractive index, extinction coefficient, real and imaginary dielectric constant) by determined using Measurement absorption and transmission spectra. Results showed that through the optical constants we can make to control it are wide applications as an optoelectronic devices and photovoltaic applications.

CuInSe2 (CIS)thin films have been prepared by use vacuum thermal evaporation technique, of 750 nm thickness, with rate of deposition 1.8±0.1 nm/sec on glass substrate at room temperature and pressure (10-5) mbar. Heat treatment has been carried out in the range (400-600) K for all samples. The optical properties of the CIS thin films are been studied such as (absorption coefficient, refractive index, extinction coefficient, real and imaginary dielectric constant)by determined using Measurement absorption and transmission spectra. Results showed that through the optical constants we can made to control it is wide applications as an optoelectronic devices and photovoltaic applications.