this paper is to study the CONVERGENCE of per capita income. CONVERGENCE clubs HYPOTHESIS is one of the forms of CONVERGENCE hypotheses, implying that countries with the same initial level of economic development, technology, and government policies, tend to be similar in per capita income and thus have a tendency to cluster around a small number of poles. In order to test the HYPOTHESIS of the formation of the CONVERGENCE clubs among 15 Middle East and North African (MENA) countries for the period of 1990– 2015, we used a non-parametric analysis (distribution dynamics approach). The distribution dynamics of real per capita GDP showed that “ twin peaks” were being formed in the MENA region.

The HYPOTHESIS of financial CONVERGENCE, as one of the upshots of neoclassical economic growth models, emphasizes the process of reducing the financial gap between countries, and in meantime, the speed of this CONVERGENCE is of particular importance. Hence, the main purpose of this study is to test the financial CONVERGENCE HYPOTHESIS, and to estimate the CONVERGENCE rate using the dynamic panel technique in selected countries (separately for developed countries (38 countries) and developing countries (34 countries)) based on the generalized torque method (GMM) for the period 1992-2020. According to two models (the ratio of domestic credit to the private sector (percentage of GDP) and the ratio of working capital to GDP in the whole sample and group of developing and developed countries), the results implies the financial CONVERGENCE in these countries. Also, the CONVERGENCE rate in the first model is higher in developing countries than in developed countries. However, this speed is relatively higher in the second index of financial deepening (the ratio of money supply to GDP), and is adjusted in each period to a greater extent than short-term imbalances to achieve long-term equilibrium.

This paper tests the validity of neo-classical predictions on beta and sigma CONVERGENCE across OPEC countries in terms of real per capita GDP during the time period 1970-2004. The empirical results support the HYPOTHESIS of absolute beta CONVERGENCE among OPEC countries. It means that, initially poorer countries (with low levels of GDP) grow at faster rate than initially wealthier ones. Furthermore, the speed of CONVERGENCE is estimated 4.3 percent per year. This implies that, it would take about 32 years to close the gap between OPEC real per capita GDP. The examination of sigma CONVERGENCE confirms that, dispersion of real per capita GDP levels between OPEC countries have decreased during 1970-2004. Finally, continuation of high population growth with low level of per capita income and investment would provide some obstructions for growth for OPEC countries. So the policies they should adopt must target these issues: enhancing capital accumulation either through domestic savings or foreign direct investment and investing more in human capital. At the end, according to the findings, regional strategies (i.e. in African and Middle East countries) also have positive effects on growth and CONVERGENCE.

Purpose: The present study aims to identify and explain the futures of Iranian provinces in the competition for the development of NBIC technological CONVERGENCE (synergy between nanotechnology, biotechnology, information technology and cognitive sciences) with a focus on Yazd province. Method: This research, which has been conducted with a qualitative and descriptive approach, is classified as an exploratory futures-study. In this way, the relevant research records were first reviewed to compile a list of drivers in the development of convergent technologies. The list was then refined and prioritized to identify two key drivers, with the Delphi process attended by fourteen experts. By intersecting the uncertainties of these two drivers, four scenarios of the province's future in technological CONVERGENCE competition emerged. Findings: The two key drivers affecting the success of the province in the competition for convergent technologies are: the rate of development of the innovation ecosystem and the amount of financial resources allocated to this process. Based on this, four scenarios of the future situation of the province in this field were identified, which have been named as "Vanguard", "Buyer", "Remnant" and "Hired". Conclusion: In order for the provinces to be able to succeed in the forthcoming competitions in the production and operation of convergent technologies, it is necessary to plan for strengthening the ecosystem infrastructure from now; at the same time, it is necessary to make efficient efforts to provide sufficient financial resources for the research and commercialization of these technologies.

Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local model training servers for each region and a central aggregation server to form a global model in IoT networks. This article presents a novel approach to optimize data transfer and CONVERGENCE time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and model accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing data transfer and CONVERGENCE time, leading to improved performance in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.

In this study, the effect of government credit intervention in the banking system on the growth of economic sectors and its CONVERGENCE in the Iran economy during the period 1998-2018 was investigated. For this purpose, the ARDL Panel model and the beta CONVERGENCE function were used. The results showed that government credit intervention in the banking system (through the variables of payment facilities of specialized banks to their respective sector, the share of each specialized bank in the total banking system and state ownership of banks) had a significant effect on economic growth and value-added CONVERGENCE. Findings of the beta CONVERGENCE function estimate showed that the beta CONVERGENCE coefficient without considering the effect of government credit intervention was-0. 31 and considering it was-0. 67, which indicates the value-added beta CONVERGENCE between economic sectors. CONVERGENCE rate has also increased from 0. 017in the case without government credit intervention to0. 052in the case of government credit intervention. The specialization of banks with the aim of economic growth in various sectors can lead to the creation and increase of CONVERGENCE rate in Iran's economy sectors. Therefore, it was suggested that the facilities granted to the economic sectors be proportional to their share of GDP, employment and especially the total productivity of production factors.

This article is not included in your organization's subscription. However, you may be able to access this article under your organization's agreement with Elsevier.CONVERGENCE HYPOTHESIS implies that the per capita income growth rate of poor countries is higher than the rich countries. Therefore, income inequality will be decreased in transition process.This article aims at testing the club CONVERGENCE HYPOTHESIS in MENA region during 1970-2003. We use b CONVERGENCE and s CONVERGENCE (or distributed) models.Our estimation results show that the income inequality decreased during 1970-2003. Even though such decreasing was not evenly distributed. Also, in estimating b CONVERGENCE model, the coefficient of threshold dummy variable shows that per capita income in MENA region is separated in to two groups. Therefore, the club CONVERGENCE HYPOTHESIS is not rejected in MENA countries.By using panel data method, we estimate TFP in MENA region for decades of 1970,s, 1980,s and 1990,s. The results show two income groups appear in MENA. As Quah, TFP separating is one of the most important club CONVERGENCEs.