Given the importance of increasing economic openness transport companies’ face various issues arising at present time, this required importing different types of goods with different means of transport. Therefore, these companies pay great attention to reducing total costs of transporting commodities by using numbers means of transport methods from their sources to the destinations. The majority of private companies do not acquire the knowledge of using operations research methods, especially transport models, through which the total costs can be reduced, resulting in the importance and need to solve such a problem. This research presents a proposed method for the sum of Total Costs (Tc) of rows and columns, in order to arrive at the initial solutions accepted by its algorithm and compare the solution with a set of solutions that were reached through classic methods studied previously. Moreover, this research aims to compare results obtained using the proposed method versus the optimal solution after testing using the modified distribution method (MODI), and the percentile deviation scale, these tests were used to measure the efficiency of the solution for the proposed method with the optimal solution .It was concluded that the proposed method is the easiest with the least iterations number of calculations, which in turn resulted in reaching the optimal solution in transporting the optimal quantities and reducing total costs of transportation from various sources to the requesting destinations. Thus, the proposed method can be used by the companies operating in importation-exportation field to find optimal solutions for the transportation of various commodities
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Abstract
Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model
In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies. In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul
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Vocational education is the basis of contemporary educational movement that aims at satisfying human needs. Societies can develop their human resources via setting programs for the working class as an aspect of the comprehensive national development. Vocational education is the main source of technical cadres the Iraqi labor market requires of the vocational preparatory schools to provide after three years of schooling.
The vocational schools of the governorate of Basra have a number of problems that lead to the lack of proficiency of their graduates. This study is an attempt to identify these problems or obstacles
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Urinary tract infection is a bacterial infection that often affects the bladder and thus the urinary system. E. coli is one of the leading uropathogenic bacteria that cause urinary tract infections. Uropathogenic E. coli is highly effective and successful in causing urinary tract infections through biofilm formation and urothelial cell invasion mechanisms. Other organisms that cause urinary tract infections include members of the Enterobacteriaceae family, streptococci and staphylococci species and perch. In addition, K.penumoniae is another important gram-negative bacterium that causes urinary tract infections. With the PCR technique, unseen bacterial species can be detected using standard clinical microbiology methods. In this study, the
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