فهرست مطالب m. hamedi

The purpose of this article is to model the effective variables and scenarios of emergency evacuation during crises such as war and earthquake. The research method is descriptive-analytical in terms of problem solving and explanatory in terms of results. Random sampling method and Cochran's formula was used. Analysis has been done based on Wizard, Any Logic and Anp software. 8 scenarios with a maximum of two incompatible factors are considered for modeling in Any Logic. The critical scenario obtained from the simulation was selected and the solutions were checked in the Anp software. Previous researches have examined the problem from a one-dimensional view. To select solutions and scenarios, we have used decision-making techniques and combined them with simulation. The results of Any Logic show that the fifth scenario is more critical, and the results of Anp show that the criteria of adding doors and removing obstacles with weights of 0.287 and 0.262 have the highest rank. According to the normalized weights in the sub-criteria, in the criterion of time, the escape time in the corridors and stairs (with a weight of 0.65), in the cost, executive dimension (with a weight of 0.608), in the feasibility, the ability to drive (with weight 0.8), in environmental effects, impact on the public (with a weight of 0.705) and in traffic guarantee, traffic management (with a weight of 0.756) have been ranked highest.

In recent years, many studies have been presented on the interpretation and modeling of new problems by basic models. One of the most widely used of these basic models is the Bin packing problem. Over time, the importance and power of this issue in modeling new problems becomes clearer. This paper also attempts to interpret and model ``An Ordering and assigning orders to supplier's problem'' by using one of the generalizations of the bin packing problem. There are many generalizations about the bin packing problem. In this paper, for the first time, generalization of the bin packaging problem called "developed Variable size and cost bin packing problem" is modeled, which increases the flexibility of the model in solving current problems. Because the presented model is a bi-objective nonlinear programming type and NP-hard one to be solved in a reasonable time, a well-known multi-objective evolutionary algorithm, namely a Non-dominated Sorting Genetic Algorithm (NSGA-II), is proposed. To verify the obtained solution and evaluate the performance of the NSGA-II, the rmvarepsilon-constraint method is developed in solving small-sized problems. In large-sized problems, the test problems are solved by the proposed NSGA-II. Then, the Pareto-optimal solutions are evaluated by mean ideal distance, diversification, and time metrics.

Peste des Petits Ruminants (PPR) is caused by a morbillivirus from the Paramyxoviridae family and the infected animals, especially goats, that show clinical signs of necrotic stomatitis, enteritis, and pneumonia. The PPR virus has four lineages closely related to the geographical regions. Sufficient awareness of the lineage of the virus helps monitor the disease in different regions of a country. Phylogenetic studies have led to implementing strategies against new lineages that may enter a given country from the neighboring countries. The present research aimed to study the PPR virus (PPRV) detected phylogenetically by PCR in a small ruminant flock with PPR clinical signs. The goats in a flock in Alborz province showed clinical signs of PPR, and 10% died. Oral swabs and blood samples were taken from two affected goat flocks. The RT-PCR was conducted to detect PPRV RNA, and the sequence of the obtained RNA was analyzed phylogenetically. Moreover, all the samples were positive for the presence of PPRV and belonged to lineage IV. The isolates had high homology with each other and with the isolates from different countries. To inhibit the entrance of new isolates to Iran and reduce the incidence of outbreaks in Iran, it is essential to control the animals’ movement across the borders and increase the vaccination coverage throughout the country. To eradicate PPR, an extensive vaccination program should cover small ruminant populations throughout the country.

In the rubber industry, the process of designing rubber compound is of great importance due to the impact on product specifications. The good performance of this process is a competitive advantage for manufacturers in this industry. The process of designing a rubber compound includes a set of activities related to selecting the best amount of raw materials to prepare a composition with the desired physical and mechanical properties. Currently, the most common method for designing a rubber compound is the experimental method based on trial and errors. This method is time consuming and expensive. In addition, the obtained combination is not necessarily the best combination. To improve the performance of the rubber compound we need to design the desired process, this research presented using a combination of artificial neural network and genetic algorithm, with an approach to reduce time and cost, while increasing accuracy. In this method, the behavior of the rubber compound was modeled with artificial neural network. Then, using Genetic Algorithm as a quick search technique.The optimal values of the four raw materials such as carbon, sulfur, oil and accelerator; in order to determine the specified value of the two characteristics .abrasion and rubber modulus at 300% elasticity at the lowest price. To evaluate the method, several samples of rubber compound designed with two method. The results showed that the artificial neural network model has the ability to predict the two characteristics of abrasion and modulus based on the four mentioned raw materials in the trained range with high accuracy. In addition, average results for genetic algorithm, is a price of 17% less and a design accuracy of 84.5% more than experimental method. The design speed with this method is 454 times higher than the experimental design speed. Based on the results, by designing the rubber compound with the integration of artificial intelligence and genetic algorithms has a better performance than the experimental method.

A stand-alone microgrid usually contains a set of distributed generation resources, energy storage system and loads that can be used to supply electricity of remote areas. These areas are small in terms of population and industry. Connection of these areas to the national distribution network due to the high costs of constructing transmission lines is not economical. Optimal utilization and economic management of production units and storage devices are important issues in isolated microgrids. During optimum utilization, of renewable energy harvesting is maximized and fuel cost of diesel units reduces as much as possible. In this paper, the optimization problem is designed and solved as Linear Programming (LP). The cost of diesel generator unit depends on its production. Also, the fact is considered that the efficiency of diesel generator units is not constant for all amount of production. As a solution for this challenge demand side management plans have been proposed. On the other hand, load uncertainty is considered in this paper. Several scenarios are simulated by GAMS software for different conditions of a typical microgrid. The simulation results show the success of the proposed method in reducing costs and fossil fuel consumption and increasing the consumption of renewable energy.

In this paper, the general case of an anisotropic thermo-electro elastic body subjected to static biasing fields is considered. The biasing fields may be introduced by heat flux, body forces, external surface tractions, and electric fields. By introducing proper thermodynamic functions and employing variational principle for a thermo-electro elastic body, the nonlinear constitutive relations and the nonlinear equation of motion are extracted. The equations have the advantage of employing the Lagrangian strain and second Piola-Kirchhoff stress tensor with symmetric characteristics. These equations are used to analyze the high frequency vibrations of piezoelectric resonators under finite biasing fields. A system of three dimensional equations is derived for initial and incremental fields on the body. Capability of the equations in numerical modelling of temperature-frequency and force-frequency effects in quartz crystal is demonstrated. The numerical results compare well with the data from experiments. These equations may be used in accurate modelling of piezoelectric devices subjected to thermo electro mechanical loads.

Production and consumption of whole tomato and/or its products(tomato paste, tomato juice, ketchup, etc) is incearsed all over the world. Annual production of tomato in Iran is about 3.4 million tons (MT), part of that is processed in the tomato paste factorise, which are mostly located in khorasan province. Since tomato variety has a determinant effect on the physico-chemical and organo leptical properties/quality of tomato and its products, an investigation was performed to evaluate the impact of variety and storage time of four tomato varieties, Cal.j.n.3, Early Urbana Y, Early Urbana 111and Peto early C.H which were selected according to a national project and were monitored according to their brix, pH, Acidity, Sugar and Salt contents, total and non soluble solids. Results indicated that Early Urbana 111 and Peto early C.H contained the highest amounts of soluble solids along with the highest pH. Also it was evidenced that these varieties were the most stable varieties as the least compositional changes was seen in them.

In this study, some physico-chemical characteristics of Iranian tea-seed oil (Lahijan variety) were compared with those of the oils from sunflower seed (Fars variety) and olive (Gilezeytoon variety) in terms of fatty acid contents, peroxide value, iodine value, saponification value, and oil shelf-life. Also the shelf-life of sunflower and olive oils containing 5% and 10% tea-seed oil were compared against control sample shelf-life. Tea-seed oil was found to be suitable and stable in nutritional properties. At a temeprature of 63oC, tea-seed and olive oils were found to have identical shelf-life values, which was higher than that of sunflower oil. Furthermore, the shelf-life of sunflower oil increased when mixed with tea-seed oil.