Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al- Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-

Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit.  The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al-Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah

The possibility of implementing smart mobility in the traditional city: Studying the possibility of establishing an intelligent transportation system in the city center of Kadhimiya

Several industrial wastewater streams may contain heavy metal ions, which must be effectively removal
before the discharge or reuse of treated waters could take place. In this paper, the removal of copper( II)
by foam flotation from dilute aqueous solutions was investigated at laboratory scale. The effects of
various parameters such as pH, collector and frother concentrations, initial copper concentration, air flow
rate, hole diameter of the gas distributor, and NaCl addition were tested in a bubble column of 6 cm inside
diameter and 120 cm height. Sodium dodecylsulfate (SDS) and Hexadecyl trimethyl ammonium bromide
(HTAB) were used as anionic and cationic surfactant, respectively. Ethanol was used as frothers and the

Nanocrystalline copper sulphide (Cu2-xS) powders were synthesized by chemical precipitation from their aqueous solutions composed of different molar ratio of copper sulfate dehydrate (CuSO4.5H2O) and thiorea (NH2)2CS as source of Cu+2, S-2 ions respectively, and sodium ethylene diamine tetra acetic acid dehydrate (EDTA) as a complex agent. The compositions, morphological and structural properties of the nanopowders were characterized by energy dispersive spectroscopy (EDS), scanning electron microscope (SEM), and X-ray diffraction (XRD), respectively. The compositional results showed that the copper content was high and the Sulfur content was low for both CuS and Cu2S nanopowders. SEM images shows that all products consist of aggregate o

        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E₁ , E₂ , E₃)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).