A new Turbidimetric method characterized by simplicity, accuracy and speed for determination of Hydronium ion by continuous flow injection analysis. The method was based on the formation of complex Zn3[Fe(CN)6] for Zinc(II) that was eluted by Hydronium ion from cation exchanger column with Potassium hexacyanoferrate(III) for the formation of a pale yellow precipitate and this precipitate was determined using homemade Linear Array Ayah-5SX1-T-1D continuous flow injection analyser. The optimum parameters were 2.7 mL.min-1 flow rate using H2O as a carrier stream, 1.7 mL.min-1 reagent stream, 110 L sample volume and open valve for the purge of the sample segment. Data treatment shows that linear range 0.01-0.1 mol.L-1 for each acids (HClO4,HNO3,HCl,H2SO4) while L.O.D 30, 50.01,29.75,51.41 μg/sample for HClO4,H2SO4,HCl,HNO3 respectively from the stepwise dilution for minimum concentration of lowest concentration in linear dynamic range of the calibration graph. The correlation coefficient (r) was 0.9891, 0.9930, 0.9917, 0.9940 while percentage linearity (%r2) was 97.85%, 98.81%, 98.61%, 98.36% for HClO4, H2SO4, HCl, HNO3 respectively. R.S.D. % for the repeatability (n=5) was < 2% for determination of Hydronium ion with concentration 20 and 80 mMol.L-1. The method was applied successfully for the determination of Hydronium ion in commercial samples. Using paired t-test between the newly developed method and classical method; shows that there were no significant differences between either methods. On this basis the new method can be accepted as an alternative analytical method for determination of Hydronium ion in commercial samples.
Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute
... Show More
(36)
(24)
A method for Approximated evaluation of linear functional differential equations is described. where a function approximation as a linear combination of a set of orthogonal basis functions which are chebyshev functions .The coefficients of the approximation are determined by (least square and Galerkin’s) methods. The property of chebyshev polynomials leads to good results , which are demonstrated with examples.
(3)
The theory of probabilistic programming may be conceived in several different ways. As a method of programming it analyses the implications of probabilistic variations in the parameter space of linear or nonlinear programming model. The generating mechanism of such probabilistic variations in the economic models may be due to incomplete information about changes in demand, production and technology, specification errors about the econometric relations presumed for different economic agents, uncertainty of various sorts and the consequences of imperfect aggregation or disaggregating of economic variables. In this Research we discuss the probabilistic programming problem when the coefficient bi is random variable
... Show More
Phenol condensed with β-keto esters via Pechmann condensation to form derivatives of Coumarin in various reaction conditions by two ways. Present paper is comparative study of synthesis Coumarin with the yield of product , reaction time and reaction conditions.
The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
... Show More
(1)
(11)
(11)
(1)
(1)