درخت حوزه‌های تخصصی

EXTENDED ABSTRACT INTRODUCTION The purpose of this study is to analyze the concept of "developed man" and determine the degree to which attention is paid in the Fundamental Transformation Document (FTD) in education in Iran approved in December 2011. This concept has been developed based on the theoretical basics of classical economics on description of "economic man" and also the Engels’s theory on the description of "modern man" and with regard to some of adapted and localized national and Islamic ideas and beliefs. What is meant by "Developed man" in this research is a person whose attitude and opinion has been developed and has the ability to turn the country's resources into wealth and prosperity for the people of society.  METHODOLOGY The instrument by which one can measure it, is a researcher-made content analysis checklist that involves 25 characteristics for developed human, and its face reliability and validity have been also verified and ranked by subject matter experts. Shannon entropy indices have been used to determine the importance and ranking of developed human components. In order to achieve a valid explanation and transparent results in this study, some important and fundamental concepts and components that were analyzed in the literature reviewing this document and their frequency was determined, were selected, and their frequency was compared with the total frequency of developed human components in the transformation document text. FINDINGS By use of word-counting the whole text of the Fundamental Transformation Document of education system, it also became evident that only about 1% (113 words out of 10914 words available) of this 64-page document are dedicated to the components of developed human and as a result it can be said that with regard to the weight and importance of the economy and its related issues in the country (such as unemployment, weak attitudes and skills of wealth creation and lack of efforts to increase production and improve public living and poverty alleviation) from the leaders and policymakers viewpoint, especially. CONCLUSION In recent decades, little emphasis and attention has been paid to developed human, and accordingly, it is worthwhile to pay close attention to these components in revision of the Transformation Document text.

The theory of relative purchasing power parity to determine the long-run trend of the exchange rate in Iran is quite sensitive to the base year selection. So, by changing the base year, trends with a level difference of several hundred percent are obtained. It means that the long-run trend of the real exchange rate is not at a constant level. In other words, contrary to the PPP theory, the real exchange rate trend is not stationary. Empirical studies consider the non-stationary change in terms of trade resulting from the changes in the real oil price as one of the reasons. This study examines the nexus between the real exchange rate and terms of trade in Iran from 1960 to 2020, using the autoregressive distributed lag approach to cointegration as the estimation method. We find that higher terms of trade lead to a decline in the actual exchange rate and vice versa. The results indicate a long-run relationship, which means that the condition needed to estimate the long-term trend of the exchange rate in Iran is to have the same terms of trade in the base year.

Objective: Due to the importance of the relationship between the state and the university, which indicates the governance model of the university, this paper first determined the characteristics of the different models of university governance and then examined and identified the models of governance of Iranian universities during six development plans. We considered three governance models (state-centered model, Humboldt model, market-oriented model). Methods: Quantitative content analysis was used in order to evaluate the six development plans of Iran regarding different governance model. Results: The results show that the most frequencies for state-centered model presented in the first Development Plan and the most emphasis of Humboldt model was on the fifth Plan. The component frequency of the market-oriented or entrepreneurial governance dimensions in the Iranian development plans indicates that this model was considered for the first time in the third plan and the emphasis on this model in the development plans shows an increasing trend. Conclusions: The estimation of the weighting indicators showed that the emphasis of the development plans on turning to the market-oriented or entrepreneurial model in decision making is increasing, so we suggest that more researcher in their study consider transition toward third-generation universities in Iran as a developing country.

Agriculture plays a pivotal role in Africa's development and is essential for achieving the Sustainable Development Goals (SDGs). However, the agricultural sector is inherently exposed to production risks, and many farmers in the developing world lack access to reliable agricultural insurance coverage. This situation arises due to limited data and knowledge about farmers' insurance needs and the high costs associated with insuring against severe agricultural risks. Promoting agricultural insurance as an instrument can have several significant impacts, aligning with multiple SDGs. It can help stabilize farmers' income, thereby contributing to the goal of reducing poverty (SDG 1). Moreover, agricultural insurance can provide a safety net for food producers, helping them manage the impacts of climate-related risks and aligning with SDG 13, which addresses climate action. Additionally, by enhancing the resilience of farmers and ensuring more predictable income, agricultural insurance can contribute to addressing hunger (SDG 2) and ultimately create a more sustainable and prosperous agricultural sector in Africa. Therefore, this study evaluated agricultural insurance as an instrument for sustainable food supply systems in Nigeria. This study adopted a survey design. This study captured thoughts, experiences, and observations of selected agricultural underwriters in the Nigerian insurance industry through structured questionnaire. A descriptive statistic was employed in the data analysis. This study results indicated that aside from farmers’ awareness which showed some level of yardstick with respect to farmers behavioural metrics, all other metrics played no significant roles. It was also recorded that why farmers’ age, gender, family size and farming experience have no significant roles in the uptake of agricultural insurance, all other participatory factors have major effects. The study contributed significantly to knowledge with the graphical representations of the challenges confronting the agricultural insurers in Nigeria. The study provided suitable recommendations that endear achievable SDGs in Nigeria.

Detecting financial fraud is an important process in the activities of compa-nies. In the last decade, much attention has been paid to fraud detection techniques. Financial fraud is a problem with far-reaching implications for shareholders. Today, financial fraud in companies has become a big prob-lem. Companies and regulatory agencies must continuously develop their mechanisms to detect fraud. Machine learning and data mining techniques are currently commonly used to solve this problem. However, these tech-niques still need to be improved in terms of computational cost, memory cost, and dealing with big data that is becoming a feature of current financial transactions. In this research, machine learning techniques including logistic regression, neural network, and Bayesian linear regression were used to de-tect financial frauds in the Iranian stock market. According to the obtained results, the support vector machine model with radial kernel has the lowest RMSE and the highest accuracy criterion, and the support vector machine model with linear kernel and Bayesian linear regression has the highest RMSE and the lowest accuracy criterion for modeling the financial fraud of companies in they were Tehran stock market. Also, the models of artificial neural network model, Bayesian linear regression and support vector ma-chine model with linear kernel respectively had the lowest characteristic values and did not perform relatively well in detecting the existence of fi-nancial fraud in the companies present in the Tehran stock market.