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.

The study designed the facilitator mechanisms model for changing Deputy of Technological Affairsin IRIB based on the qualitative method grounded theory. Data collected by semi-structured interview through snowball sampling method, and were analysed in three stages of coding: open, axial, and selective. In the research, 9 managers and experts of IRIB were interviewed. The model comprised different components: 450 initial codes, 48 conceptual codes, and 14 categories in six groups. “ The emergence of Technological Convergence space” selected as prerequisite and “ the need to redesign the Deputy of Technological Affairs structure” as the main phenomenon of the model. It was introduced "Changing the activities of Technological Deputy" as strategy and "legal mechanisms" as intervening conditions. "Making competitive thinking" provides a context for redefining the activities of the Technological Deputy. The last component of the model derived from the categorization was "Designing Facilitator Mechanisms for Changing Structure". According to research findings, many activities of the Deputy of Technological Affairs does not match the characteristics and requirements of the Technological Convergence era. Operations such as identifying non-target activities and deputing them, employing multi-tasking human resources, are essential in developming and agility of the structure.

The basis of human life in the inhabited biosphere is the balance in the triple cycle of water, food and energy. Also, fair use and exploitation of land and natural resources are added to this importance. However, due to human and artificial carelessness, irreparable events appear that significantly impact the failure of the human life cycle. We can mention climate changes that leave unlimited environmental crises among these events. This is not a marginal issue, but it is considered an ongoing and crucial global issue. This research attempts to analyse the gaps in tools in the field of responsibility and the necessity of international partners in the light of diplomacy by enumerating the upcoming events and sufferings. This research seeks to answer how the climate Convergence model is realised in its two-way relationship with the triple cycle. With this description, the importance of climate change and its direct and indirect effects on vital human dimensions made us look at this issue.

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.

Modern communication technologies has resulted in globalization of the media industry while changing the basis of the economy of the industry and management of the media agencies, so that this change has relentlessly developed the workforce of the media companies. The issue has also changed the regime of industrial economy to a service economy. These changes have therefore created new agencies and caused their merger in various sectors of the media market and ultimately created developments in the principles of the global trade.Technological Convergence also helped the global trend to privatize the communication industries and remove regulations from them, so these processes reduced most of the media restrictions on the foreign investment markets, or totally removed them.The present research has used the (Q) method to familiarize with the viewpoints of experts on the theory of media Convergence in the Islamic Republic of Iran.The present research extracted 52 speeches from the heart of the theories. Then 25 experts and lecturers of the technology management with the minimum rank of assistant professor were selected to complete the above speeches. The procedure was followed by Quanell computer program to find out the Pearson coefficient of correlation among the 25 technology management experts. An “operative analysis” was also conducted after the calculation of the coefficients of correlation and necessary date were extracted after clarification of the speeches under the study.

Technological entrepreneurship ecosystem (TEE) is comprised of various elements and complex relations that all interact with each other to enable the creation and growth of Technological entrepreneurship. The Technological entrepreneur, as the main constituent of this ecosystem, should possess specific characteristics and also must perform particular roles. Despite the importance of (tech) entrepreneur in the (Technological) entrepreneurship ecosystem, we are facing with the lack of comprehensive and robust literature in this domain. The aim of this research is to identify and explain various roles of tech-entrepreneurs in the relevant ecosystem. In this path, we adopted a constructivist approach of grounded theory, conducted in-depth interviews and analyzed secondary sources. Totally, we analyzed 27 cases of Technological entrepreneurship process that ended in the identification of 14 specific roles in three groups. First, the principal roles which are research & development, market analysis, and resource mobilization. Second, the supporting roles such as networking, incident monitoring, and cooperation with technical experts. Third, the general (contextual) roles like building trust, and proper interactions with other elements of the ecosystem. These roles which based on their nature are in relation and interaction with other elements of the ecosystem, can enhance the related literature of entrepreneurship ecosystem and also lead the actions of Technological entrepreneurs.