In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better
Transportation Sector classified as one of the services sectors which is without the production activities cannot be complete its rule. Is act asmoving actions which operate at production and non production goals for the organization and individuals insides the country and with others, that is why this sector act as one of the main which is occupied an important status on the way the economic activities and on the level of the economic institutions the transportation work on transforming all the commodities and products from productions locations to consumption location then its effect the productivity process and create the location utility and on the level of economic it considered as one of the economic supportive structure an
... Show MoreThis paper aims at presenting a comparison between objective and subjective tests . This paper attemptsto shed light on these two aspects of tests and make do a compression by using suitable techniques for objective and subjective tests .
The paper compares between the two techniques used by the objective and subjective tests respectively, the time and efforts required by each type, the extent to which each type can be reliable, and the skills each type is suitable to measure.
The paper shows that objective tests, on the contrary of the subjective ones, encourages guess> Objective tests are used to test specific areas of langua
... Show MoreIn this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.
The research aims to evaluate the suppliers at Diyala general electric industries company conducted in an environment of uncertainty and fuzzy where there is no particular system followed by the company, and also aims to use the problem of traveling salesman problem in the process of transporting raw materials from suppliers to the company in a fuzzy environment. Therefore, a system based on mathematical methods and quantity was developed to evaluate the suppliers. Fuzzy inference system (FIS) and fuzzy set theory were used to solve this problem through (Matlab) and the problem of the traveling salesman in two stages was also solved by the first stage of eliminating the fuzzing of the environment using the rank function method, w
... Show MoreBackground: Male infertility is a global concern and it tends to increase due to miscellaneous factors, such as environmental toxins and genetic and lifestyle choices. The aryl hydrocarbon receptor (AHR) has recently attracted attention due to its involvement in male infertility mechanisms and impact on sperm production and function. AHR, a versatile receptor expressed in various tissues, including the testes, regulates the genes involved in spermatogenesis. AHR activation is associated with cell cycle regulation and chromatin condensation during spermatogenesis. Objectives: This study aimed to investigate the influence of AHR activation on blood-testis barrier (BTB) integrity, focusing on the role of tight junction protein-1 (TJP1)
... Show MoreIn this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).