جستجوی مقالات مرتبط با کلیدواژه « شبیه سازی » در نشریات گروه « علوم انسانی »

According to Article 16 of the Knowledge-Based Production Leap Law, all industries that consume more than 2 megawatts of electricity must use 5% of their electricity consumption from renewable energy within 5 years. The model is optimized from the transient simulation method using Transis software, using the test design method, with the help of the response surface method. Two independent factors, the area of the solar panels and the power of the diesel generator have been selected as the main variables, and then the total electricity consumption, the total gas consumption, the total diesel fuel consumption, as well as the return on investment have been selected as the economic answer for optimization. It shows that increasing the area of solar panels with a low slope increases the investment return period. On the other hand, increasing the power of the diesel generator to about 2000 kilowatts helps to reduce the investment return period. But increasing the power of the diesel generator from 2000 to 3000 kilowatts increases the period of return on investment. Optimization using the response surface method showed that the optimal point occurs in the panel area of 11716.89 square meters and in the diesel generator power of 1986.69 kilowatts, the return on investment is 1.612 years, the results showed that the maximum value of the utility function is 0.725. which is a number very close to the maximum possible value (that is, the ideal state whose utility function is equal to 1

The main objective of the present study was to design a simulation model for development of organizational citizenship behavior (OCB) in Gas Company of Yazd province. A mixed method (qualitative and quantitative) approach was carried out in this research which was applied in terms of purpose and descriptive-analytical in terms of nature and method. In the qualitative step, the statistical population included university faculty members, managers, assistants, and experts of Yazd Gas Company, and in the quantitative part, it included university faculty members. Moreover, in the qualitative part, snowball sampling was performed until reaching theoretical saturation, and in the quantitative part, it was done by judgmental sampling. The data collection tools were interviews and questionnaires. In the qualitative section, using thematic analysis method, the effective factors on OCBs were identified. Then, the identified effective factors were prioritized using the fuzzy Delphi method, and finally, in the quantitative section, the organizational citizenship behavior development model was simulated using agent-based modeling approach. The data analysis led to the identification of 50 initial codes, 16 sub-themes and 4 main themes as below: individual, managerial, organizational and environmental factors. According to our results, managerial factor was recognized as the most effective factor. The simulation results illustrate that the presented model can provide an appropriate assessment of the future development of OCB in Gas Company of Yazd province

The pan evaporation is used as a practical parameter in various fields, such as estimating water loss from lakes and dams, as well as estimating the Plant water requirement, especially in areas where there is no lysimeter information. Modeling this parameter can be useful in the estimation of missing data and long-term planning of water resources and agricultural development. In this research, by using an artificial intelligence model (Gene Expression Programming, GEP) and two time series models (Fourier and ARIMA), evaporation from the pan at Zayanderud dam station, was modeled in the period from 1344 to 1396 (53 years). The time series of pan evaporation on daily scale for the months of June (Khordad), July (Tir), August (Mordad), September (Shahrivar), and October (Mehr) as input to the Fourier and ARIMA models and 4 different patterns including the use of daily evaporation data 1 month, 2 months, 3 months and 4 months ago, were used as input for gene expression programming model. The results showed that the GEP model has acceptable results only in Mehr, and for other months the results are not acceptable in terms of statistical indicators. The daily evaporation estimated error was found to be 0.38 mm in Mehr. This error was acceptable based on the coefficient of determination of 0.84, the Nash-Sutcliffe coefficient of 0.83 and the Willmott's index of  agreement of 0.95. Unlike the gene expression programming model, the Fourier model provided acceptable results in all the studied months. The error values were obtained between 1.02 and 0.7 mm per day in all the studied months, which is equivalent to 5.2 to 8.8 percent. Comparing the results of the above two models with the ARIMA model showed that, the error values of the ARIMA model in all months are higher (9.4 to 19.6%) than the Fourier model, and Gene Expression Programming model. Therefore, the best model for estimating pan evaporation in October (Mehr) is the Gene Expression Programming model and in the rest of the months, the Fourier model. The evaluation of the model in estimating the extremes daily evaporation data also showed that the highest and lowest accuracy is in October (Mehr) and June (Khordad), respectively. In total, according to the statistical indices, the ability of the Fourier model to estimate the daily evaporation in the Zayanderud dam station was proved. Therefore, this model can be recommended to estimate the daily evaporation and also to reconstruct the missing data in this station

Temperature is a significant atmospheric element that manifests climate change, specifically global warming resulting from an increase in greenhouse gas concentration. Atmospheric simulation is a critical tool in studying changes in atmospheric-climatic elements, particularly temperature.
The most commonly used tool for simulating the responses of the climate to greenhouse gas increases and examining future temperature changes is the use of climate variables simulated by coupled atmosphere-ocean models (AOGCMs). General circulation models (GCMs) are powerful tools aimed at generating climate scenarios. However, GCMs cannot provide effective information on climate simulation at local and regional scales. Therefore, the downscaling method is used to bridge the gap between local and global scales.
The current research aims to simulate maximum temperature using an artificial neural network model that adopts data from the atmospheric general circulation model (HadCM3) under RCP8.5, RCP4.5, and RCP2.6 scenarios for the Yazd synoptic station from 2006 to 2095. The independent variable, as the input to the artificial neural network, was selected for statistical downscaling using four statistical criteria: Percentile Reduction, Backward Variable Elimination, Forward Variable Selection, and Stepwise Variable Entry. Finally, the maximum temperature of the Yazd synoptic station for the next century was simulated.

The present study aims to investigate the maximum temperature of Yazd's synoptic station in the context of climate change based on valid scenarios until 2095. To achieve this, three sets of data were used: average daily maximum temperature data from Yazd's synoptic station, observed atmospheric data for the period of 1961 to 2005 (NCEP data), and simulated data from 2006 to 2095 based on release RCP scenarios. The NCEP data from 1961 to 2005 included 26 atmospheric variables that will be used as independent or predictor variables.
Modeling, simulating, and forecasting temperature based on nonlinear and chaotic time series is a challenging task. Prior studies have shown that artificial neural networks (ANNs) are suitable for simulating and predicting basic processes that are not well known. It is crucial to select the correct input variables intelligently and according to the purpose of the artificial neural network's design for prediction and simulation. Accordingly, in this study, the most suitable atmospheric parameters as the input of the artificial neural network were selected by pre-processing and selecting the atmospheric variables for the base period (1961-2005) to simulate with four statistical criteria (Percentile Reduction, Backward Variable Elimination, Forward Variable Selection, and Stepwise Variable Entry). The resulting mean square error (MSE) obtained from the statistical criteria was compared, and the correlation coefficient and the similarity of the monthly time series trend of the simulated values with the target values were also analyzed. The best network architecture was selected to simulate the maximum temperature of Yazd's synoptic station from 2006 to 2095 under different RCP emission scenarios.

The selection of explanatory variables for downscaling was based on four statistical methods Percentile Reduction, Backward Variable Elimination, Forward Variable Selection, and Stepwise Variable Entry. After analyzing the mean square error (MSE), correlation coefficient, monthly average values of the maximum temperature of Yazd station, and estimated values from 1961 to 2005, the probability density function, cumulative probability function, and monthly time series trend obtained from all four methods, the explanatory variables were selected. These variables include mean sea level pressure, the divergence of 1000 hPa, zonal wind component, zonal wind intensity of 850 and 500 hPa, altitude and vorticity of 500 hPa, average temperature, and relative humidity at a 2 m height.
The structure and architecture of the neural network were designed based on these selected variables. The network consisted of a two-layer feedforward, with a sigmoid transfer function in the hidden layer, a linear function in the output layer, an input layer with eight variables, eight neurons, and the Lunberg-Marquardt training algorithm. This architecture was used to simulate the maximum temperature of Yazd's synoptic station under RCP2.6, RCP4.5, and RCP8.5 scenarios for two periods of 2050-2006 and 2095-2051.
Comparing the monthly average values of RCPs (RCP2.6, RCP4.5, and RCP8.5) in the first statistical period (2050-2006) with the base period (1961-2005), the maximum temperature of Yazd station indicates an increase in temperature in winter, spring, and summer, and a decrease in the autumn season under all three RCPs.
Comparing the monthly mean values of RCPs (RCP2.6, RCP4.5, and RCP8.5) of the second period (2051-1995) with measured mean maximum temperature (2005-1961) showed that temperature will increase the most in winter, spring, and summer, similar to the first period of the RCP8.5 scenario. In this scenario, unlike the other scenarios, the increase in temperature is evident in both subperiods for the autumn season. Finally, in the second period (2051-1995), the increase in the average maximum temperature of Yazd station in winter, spring, and summer, and the decrease in the average maximum temperature in autumn will be more significant.

The increase in greenhouse gas concentration resulting from human industrial activities is expected to cause global and regional warming in the future. The current study's findings indicate that the average maximum temperature of Yazd station will rise between 0.4 to 6.9  in winter, 0.2 to 8.1  in spring, and 1.1 to 7.7 in summer from 2006 to 2095. However, a decrease in the maximum temperature between 0.6 and 1.4  is expected in autumn. These results are consistent with those of other researchers.

Applying a favorable tax system has important conditions such as justice and efficiency, therefore, consumption tax and income tax will comply with the principles of benefit and ability to pay. In this regard, value added tax is known as the most important innovation of the 20th century in terms of tax collection on consumption. Since increasing government revenue is one of the important goals of imposing this type of tax, the government has tried to determine the rate of this type of tax effectively and efficiently. Disproportionate increase in value added tax rates can have negative social effects on inflation, economic growth, income distribution, and general well-being in society. It may also have disruptive effects on other variables and sectors of Iran's economy. To manage the rate increase, one approach is to simulate and examine its consequences and effects on macroeconomic variables in the form of a multi-regional calculable general equilibrium model (MRCGE). Three different scenarios were applied and examined to simulate the shock effects of the increase in the value-added tax rate (12% , 15% , and 20 %) on four macro variables of Iran's economy: inflation, gross domestic product, consumption, and investment.  The simulations were conducted at the country level using a multi-regional calculable general balance model, known as the ORANI-G Iran model, using the 2016 input-output table and regional accounts of the country. The results indicate that the effect of increasing the tax rate on value-added will increase inflation and investment and decrease GDP and consumption.

There is good reason to expect crude oil prices to follow nonlinear models. However, previous research has considered the linear assumption to investigate the existence of a unit root. Unit root linear tests such as ADF, PP, and KPSS are provided for linear models. These tests are not suitable for nonlinear time series. Because the model deviation from the linear state may be considered as a random permanent deviation. The purpose of this article is to test the nonlinear unit root of crude oil prices, specifically Brent and WTI oil in the period 2019-2020 daily. For several decades now, various classes of nonlinear models have been introduced. These models introduce a wider range of dynamics than linear models in time series. A special type of these models that economists pay attention to are TAR models. In these models, as in linear models, valid statistical analysis requires distinguishing between the deterministic trend and the stochastic trend. In this study, the Bayesian unit root test for the general SETAR (1) model has been used with respect to the necessary and sufficient conditions for the maintenance of SETAR processes based on the article by Petrocyl and Wolford (1984). A nonlinear unit root test was performed using Bayesian validity interval. The results show that Brent crude oil prices in both regimes contain a unit root that is consistent with similar findings for the production or consumption of crude oil..

The main purpose of this study was to mapping the canopy cover (CC) and the aboveground net primary production (ANPP) of plant life forms by the independent factor of physiographic in the rangelands of Ardabil province.Material &

First, according to plant types and environmental factors, sampling was taken at the peak stage of plant growth from 2016 to 2020 using one square meter plots. To determine the most effective environmental factor in the changes of plant parameters, the correlation between dependent and independent variables was used. Linear regression equation was used for modeling by the most effective factor and the maps were simulated. The accuracy of the equations was also calculated by RMSE. Then, the correlation between CC and ANPP of life forms and the total was obtained.

The results showed that the elevation factor had the highest correlation with the dependent variables. The difference between the estimated average of the model with the measured values for CC of grasses equal to +1%, forbs –1%, shrubs -1%, and total CC +2%; and these values for the ANPP of grasses equal to +21 kg/ha, forbs was equal to zero, shrubs were -13 and the total ANPP was +274 kg/ha.

Predicting the studied parameters will be necessary to manage the balance between supply and demand of rangeland products.

The most important and perhaps the main concern of human rights has been formed with the emergence of new capabilities in the scientific and technological fields of biology. This has caused opposition to human simulation in jurisprudence and law. The purpose of this article is to examine the reasons for banning human cloning from the point of view of jurisprudence and criminal law. The current article is a descriptive analysis and has investigated the mentioned topic using the library method. The findings indicate that interference in God's creation, disintegration of the family system, ambiguity in kinship relations and disruption of the kinship status of cloned people are the most important jurisprudential reasons for banning human cloning. The guarantee of individual rights and freedoms of citizens based on bioethics is shown in the framework of principles that are called “bioethics principles”. These are the principles and goals that criminal law pursues in bioethics. The principle of harm, or in other words, the principle of harm, is one of the prominent principles of bioethics, which has received the most attention and discussion in the field of criminal law, and is one of the fundamental foundations of criminal law intervention. The other face of this principle appears in the field of criminal law in the form of “obligation to do no harm” and emphasizes the absence of harm.

The purpose of this paper is to examine how money is created by recording accounting events in the balance sheets of banks. Therefore, a hypothetical economy, comprised of a central bank, a gharzolhasaneh bank, a commercial bank, and the people has been simulated. We pay special attention to special accounting records in the balance sheet of a commercial bank, interest rates and deferred bank loans in the banking system and their effect on the money creation process.  According to the results, the combined use of accrual basis of accounting in identifying uncollected facility income and cash basis of accounting in the payment of interest on deposits in a commercial bank leads to the money creation in the banking system and the higher the interest rate on deposits, the more money will be created. This will not happen in gharzolhasaneh Bank due to non-payment of interest on deposits and non-use of accrual basis of accounting system in identifying the income of paid loans. Also, in case of non-repayment of granted facilities and creation of deferred bank loans, the accrual basis of accounting system allows the commercial bank to continue the process of identifying facility income and paying unrealized interest on deposits, and interest paid on deposits enters the banking system as the new created money.

Severe climate changes (and global warming) in recent years have led to changes in weather patterns and the emergence of climate anomalies in most parts of the world. The process of climate change, especially temperature changes, is one of the most important challenges in the field of earth sciences and environmental sciences. Any change in the temperature characteristics, as one of the important climatic elements of any region, causes a change in the climatic structure of that region. The summary of the investigated experimental models on climate change shows that if the concentration of greenhouse gases increases in the same way, the average temperature of the earth will increase dangerously in the near future. More than 70% of the world's CO2 emissions are attributed to cities. It is expected that with the continuation of the urbanization process, the amount of greenhouse gases will increase. According to the fifth report of the International Panel on Climate Change, the average global temperature has increased by 0.85 degrees Celsius during 1880-2012. Therefore, knowing the temperature changes and trends in environmental planning based on the climate knowledge of each point and region seems essential. For this reason, the present study simulates the daily temperature (minimum, maximum and average) of Zanjan until the year 2100.

The method of conducting the research is descriptive-analytical and the method of collecting data is library (documents). To check the temperature of Zanjan city, the minimum, maximum and average daily temperature data from Hamdeed station of Zanjan city during the period of 1961-2021 were used. The data of general atmospheric circulation model was used to simulate climate variables (minimum, average and maximum temperature) using artificial neural network and climate scenarios in future periods. The output variables in this study are minimum, maximum and average daily temperature. Therefore, three neural network models were selected. For model simulation, model inputs (independent variables) need to be selected from among 26 atmospheric variables. Therefore, two methods of progressive and step-by-step elimination were chosen to determine the inputs of the model. In these methods, climate variables that have the highest correlation with minimum, maximum and average daily temperature were selected. By using RCP2.6, RCP4.5 and RCP8.5 scenarios, variables were simulated until the year 2100. Markov chain model was used to check the possibility of occurrence of extreme temperatures of the simulated values.

According to the RCP2.6, RCP4.5 and RCP8.5 scenarios and the simulation made by the neural network model, it is possible that on average the minimum temperature will be 3.6 degrees Celsius, the average temperature will be 3.3 degrees Celsius and the maximum temperature will be 2.7 degrees Celsius. Celsius will rise. The monthly review of the simulated data for all scenarios and the observed data of the studied variables shows that the average minimum, average and maximum temperatures in January and February, which are the coldest months of the year, will increase the most and become warmer. While the average minimum temperature in August, the average temperature in April and the maximum temperature in October will have the least increase. According to the simulated seasonal temperature table based on all scenarios, it was found that the average minimum, average and maximum temperature observed with the maximum simulated conditions were 6.9, 5.5 and 5.4 respectively in the winter season, and 3.3 in the spring season. 4, 2.3 and 3, in the summer season it increases by 3.3, 3.4 and 1.4 and in the autumn season it increases by 4.6, 4.5 and zero degrees. The frequency of extreme temperatures observed in all three variables of minimum, average and maximum temperature for the 25th and 75th quartiles is less than the number of occurrences of extreme temperatures simulated in all three scenarios. Based on this, all three variables will increase and there will be fewer cold periods. An increase in night temperature and average temperature in winter season and maximum temperature in summer season will occur more than other seasons. The difference between day and night temperature will be less in autumn and summer. Also, all seasons, especially the summer season, will be hotter and the occurrence of extreme temperatures is increasing for the coming years.

Adequate comprehension of the challenges and influential elements of the religious tourism sector is necessary for its positive development. In this regard, the present research was conducted to present a model that can simulate the development of religious tourism in Yazd province by considering the influential factors. A mixed method (qualitative and quantitative) was carried out in this study, and the research method was applied in terms of purpose and descriptive-analytical in terms of nature. The statistical population of this research included 12 theoretical and experimental experts. Questionnaires and interviews were used to collect data with non-random and purposeful sampling. In the qualitative section, the main and sub-categories of religious tourism development in Yazd province were identified using the thematic analysis method. Then, in the quantitative part, the identified influential factors were prioritized using the interpretive structural modeling (ISM) method. Finally, the criteria obtained from the qualitative research analysis were simulated using the agent-based modeling (ABM) method. Based on the research results, 35 initial codes, 12 sub-themes, and six main themes (religious tourism policies, economic, infrastructure, environmental empowerment, marketing, and cultural) were identified. Religious tourism policies were recognized as the most influential factor. Also, the results showed that at the end of the simulation period, the rate of religious tourism development in Yazd Province had reached 70%. Based on the findings of this study, it is recommended that tourism managers give particular attention to the influential factors that have been identified as having a significant impact on the development of religious tourism.

Following the population control policy of international which was implemented in Iran in the last few decades, today has caused a huge change in the demographic age structure and has pushed the country's population towards an increase in the rate of old age. It has caused the dependency rate to be one of the basic challenges of policy makers in the future. Therefore, the current research has simulated the changes in the structure of the Iran's population during the years 1355 to 1455 by using dynamic systems modeling. The results of forecasting the structural changes of the population show that the country's population will reach 94132000 million people in 1426 with an average annual fertility rate of 1.6. After that, it started a downward trend and will reach 86416400 people in 1455. This is despite the fact that the elderly population will grow increasingly during this period; So that it will reach 29% of the total population. The results show that due to the unbalanced population growth of the country in three decades (60s, 50s and 70s) and the increase in life expectancy from 54 years to 76 years, in the coming decades the population structure of the country will be an aging structure and due to the increase in the rate of the dependence of the country's population will have harmful economic consequences.

project portfolio management is a framework for integrated management of projects to achieve strategic goals of companies, considering the constraints. Its significance is more apparent in uncertain conditions that prevails in Iran's oil and gas industries, which confronts with capital constraints, sanctions, and economics fluctuations. The itroduced framework in this research encompasses the identification and definition of various scenarios for each oil and gas field, determination of mathematical model parameters, necessary data for calculating the model parameters, and the process and methods for their identification. Ultimately, it leads to the development of a mathematical model, which is the distinctive aspect of this study. The research, in terms of objective, is an application with a modeling and mathematical simulation approach, to providing a model for selecting an optimal portfolio of investment projects for upstream oil and gas companies under uncertainty conditions. After collecting the required data, the mathematical programming model was designed as an integer zero-one programming model with an objective function to maximize the net present value of different field scenarios, considering investment constraints and other binding constraints. The coding of the above model was executed and the intended simulation for uncertain parameters was performed using the CRYSTALL BALL software.

Recent advances in computers, networking, and telecommunications offer new opportunities for using simulation and gaming as methodological tools for improving crisis management. Videos can be used to present scenario updates to players in “newscast” format and to present pre-taped briefings by experts to players. Organizations responsible for crisis management are already using such technologies in constructing crisis management systems (CMSs) to coordinate response to a crisis, provide decision support during a crisis, and support activities prior to the crisis and after the crisis. The findings of the present study reveal that if designed with gaming in mind, the CMSs could be easily used in a simulation mode to play a crisis management game. Such a use of the system would also provide personnel with opportunities to rehearse for real crises using the same tools they would have available to them in a real crisis. In this paper, we provide some background for the use of simulation and gaming in crisis management training, describe an architecture for simulation and gaming, and present a case study to illustrate how virtual environments can be used for crisis management training.

Floods are occurring as an environmental hazard in many parts of the world, especially in countries that have been ineffective in crisis management and resource conservation. This natural hazard has become one of the most damaging natural disasters since the reckless activities of human beings in exploiting the natural environment have increased. One of the ways to deal with this danger is to predict the occurrence of floods. The models that are used to predict the occurrence of floods may not have the same accuracy in predicting precipitation events in different seasons of the year. Due to the importance of this issue, in this study, the results of the the Geomorphological Instantaneous Unit Hydrograph (GIUH) model in predicting floods in winter and spring in Minab catchment (Brentin) were compared. The data include the maximum hourly flow and their corresponding precipitation for three spring and three winter events. First, the required parameters of GIUH model including branching ratio, length ratio and area ratio for the basin were estimated using GIS softwar. Then, the events of winter and spring seasons, the peak discharge values, and the time of the peak discharge were compared. The results of this comparison showed that GIUH model predicts peak discharge and peak flood time occurring in winter (with average values of 20.09 and 45.64%, respectively). It is less distant from the observed data, and has a higher accuracy than spring events (with average values of 57.3 and 119.7, respectively).

During the last two decades, some international treaties have played a decisive role in facilitating scientific collaboration between member countries. For this reason, the study aims to predict the effect of Iran's membership in these treaties on three things: First, the amount of scientific collaboration between Iran and the members of each treaty; Second, the total amount of Iran's international scientific collaboration; Third, the extent of Iran's dependence on scientific collaboration with the USA, as the most key actor in the international scientific collaboration network. According to the background, the treaties that have a significant impact on international scientific collaboration are G7, G20, EU, OECD, OPEC, APEC, and BRICS. This study is based on the simulation method (with an agent-based modeling approach). This method was used to simulate the network of scientific collaboration between independent countries with more than one million people in the period of 2023-2042. The secondary data required for the simulation were collected from the Web of Science database and the United Nations database. Hypotheses related to possible scenarios were tested based on difference-in-difference statistical model. All calculations, including network simulation and hypothesis testing, were performed in the R software environment. The findings showed that Iran's joining G20, OECD, and APEC will significantly increase Iran's scientific collaboration with the members of each treaty. However, Iran's membership in the BRICS will not have a significant effect on its collaboration with the BRICS members. Also, Iran's joining each of these four treaties will significantly increase the total amount of Iran's international scientific collaboration. However, the increase in the G20 scenario is higher, and in the BRICS scenario is lower than other treaties. At the same time, Iran's membership in the G20 and BRICS will lead to a significant increase in Iran's dependence on collaboration with the USA. In return, Iran's membership in the OECD and APEC will play a significant role in reducing Iran's dependence on collaboration with the USA. Another advantage of Iran's membership in the OECD is strengthening its collaboration with two of the key players in Europe (France and Italy). One of the side benefits of Iran's joining APEC is the significant increase in its collaboration with the key player in East Asia (China). The results indicated that Iran's joining OECD and APEC will help to increase Iran's visibility in the international scientific collaboration network and reduce Iran's dependence on collaboration with the USA.

This study aimed to design a model for the impact of guerrilla marketing on attracting the customers of sports stores in Yazd Province, Iran. Utilizing an exploratory, mixed-methods research design, this study was thus performed in accordance with inductive-deductive reasoning. The statistical population comprised of the university professors and managers of the sports stores in Yazd Province, Iran, selected by snowball sampling until theoretical saturation occurred (N=12). The data collection tools included interviews and questionnaires. During the qualitative phase, the main categories (themes) and subcategories (subthemes) of the guerrilla marketing tools were initially isolated using thematic analysis. Afterward, the given tools were prioritized with the fuzzy Delphi method. Ultimately, the impact of the guerrilla marketing tools on attracting the customers of sports stores was simulated in the quantitative phase, through agent-based modeling. The data analysis was carried out during the qualitative phase via MAXQDA 20 and Microsoft Excel, and that was completed in the quantitative phase by the use of AnyLogic. With reference to the study results, 36 primary codes, eight subcategories (sub-themes), and four main categories (themes), namely, cultural tools, human tools, technology tools, and customer attraction tools were identified, and then the cultural tools were acknowledged as the most effective ones. Besides, the simulation results demonstrated that the proposed model could provide the proper estimate of the future of attracting the customers of sports stores in Yazd Province, Iran. Along with the study results, the managers of sports stores are suggested to reflect on the guerrilla marketing tools identified here in order to attract more customers.

The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, a state diagram was obtained. Using the state diagram, initial sampling, systematic review of sources and results of interviews, 9 conceptual agents "governance organizations, management and leadership, clinical personnel, support personnel, hospital infrastructure, assessor, standards, assessment method and service recipient" were identified. Finally, the conceptual model of agent-based, environment, behavioral rules of agents and their input and output interactions was presented. In future researches, reinforcement learning models can be designed according to the conceptual model of this study, so that by using it, software developers can develop a suitable framework for solving complex problems in the field of hospital accreditation. Because the field of hospital management systems is one of the desirable types of socio-technical systems that have high capacities.

The purpose of this research is to investigate the effect of teaching with the help of multimedia created by the researcher on the academic progress of experimental 11th grade students in physics.The basis of this multimedia is a PowerPoint file. The main parts of this multimedia are:1) simulations and virtual laboratory 2) real experiment in the form of a film 3) animation 4) conceptual diagram5) Analogy 6) Augmented reality 7) Laboratory hand structures 8) Scanning every day with physicsThis software has other parts such as scientific materials, test tips, examples, exercises, activities, test yourself, check what you have learned, games and tests.This research is practical in terms of purpose and quasi-experimental in terms of implementation. The statistical sample of this research is the number of 30 experimental 11th grade students from Hazrat Ghaem Freeman State Model School in the academic year of 1402-1401, who are divided into two groups of control (15 people) and experimental (15 people). In the experimental group, teaching was done with the help of multimedia software, and in the control group, it was done in the usual and traditional way. The data of this research was analyzed with SPSS version 27 software.

The aim of the research is "designing a smart dynamic model of preventive net using simulation in interaction with production" based on the documentation of textile and clothing industries under the title of dynamic preventive net model. In order to calculate the dynamics of the system, Vansim software and research data were prepared based on a sample of 2000 data and reports from the textile and clothing industries during the years 2016 to the end of 2014 and the textile factories of Borujerd as the location of the project on a semi-annual basis. The results of the research show that the growth rate of "working environment on the net" has reached the lowest growth rate of 1.2% in 2016 and 3.5% in 2018 and a higher growth of 6% in 2014. The growth rate of "Internet technology" has reached an average growth rate of 1.2% in 1396, 5% in 1398, and a higher growth of 8.5% in 1400. The dynamic growth rate of the variable "Strategy in Net" has reached the maximum growth rate of 1% in 2016, 6% in 2018, and a higher rate of growth in 2014, i.e. 9.5% (optimal state).