In this paper, a mathematical model for the oxidative desulfurization of kerosene had been developed. The mathematical model and simulation process is a very important process due to it provides a better understanding of a real process. The mathematical model in this study was based on experimental results which were taken from literature to calculate the optimal kinetic parameters where simulation and optimization were conducted using gPROMS software. The optimal kinetic parameters were Activation energy 18.63958 kJ/mol, Pre-exponential factor 2201.34 (wt)-0.76636. min-1 and the reaction order 1.76636. These optimal kinetic parameters were used to find the optimal reaction conditions which used to obtain a high conversion (≥ 99%). These optimal reaction conditions were reaction temperature 379.4 oK and reaction time 160 min. A scale up to batch reactor was conducted using these optimal kinetic parameters and optimal reaction conditions and the results showed the best reactor size that can be used at a diameter of 1.2 m.
The current research seeks to identify the impact of Barman's model on acquisition of the concepts of jurisprudence of worship among students of the departments of Qur'anic sciences. To achieve the research objectives, the researcher relied on the experimental method through a design with partial control by relying on two experimental groups receiving teaching by using the Barman model and a control group receives teaching through the normal method. After applying the experiment, the study reached the following results: Students of the Department of Qur’anic Sciences in general need educational programs linked to the curriculum and built on scientific foundations, according to their needs and problems (psychological, cognitive, and soc
... Show MoreThis research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),
... Show MoreThe objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).
A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions and Middle East. Empirical studies that dealt with people/healthcare worker (HCW) perceptio
The objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).
A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions and Middle East. Empirical studies that dealt with people/healthcare worker (HCW) perceptio
Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.
We compare two methods Bayesian and . Then the results were compared using MSe criteria.
A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.
... Show MoreThis study aims to analyze the spatial distribution of the epidemic spread and the role of the physical, social, and economic characteristics in this spreading. A geographically weighted regression (GWR) model was built within a GIS environment using infection data monitored by the Iraqi Ministry of Health records for 10 months from March to December 2020. The factors adopted in this model are the size of urban interaction areas and human gatherings, movement level and accessibility, and the volume of public services and facilities that attract people. The results show that it would be possible to deal with each administrative unit in proportion to its circumstances in light of the factors that appe