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Copyright of International Journal for Research & Educational Development is the property of Ithra Elmarafa for Conferences, Researches & Scientific Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research aims to study and analyze the role of adopting artificial intelligence technologies in supporting the predictive ability of financial statements in the context of big data. To achieve the research objective, the researchers designed a questionnaire that included three axes related to the research variables. It was distributed electronically to a sample of accountants, auditors, and investors in the Iraq Stock Exchange. Around 70 responses were collected from the sample members and relied upon in the practical aspect of the research. The SPSS statistical program was used to analyze the results. The research found that artificial intelligence technologies have a statistically significant effect in improving the predictive value of accounting information, and this effect increases in light of big data. Among the most important recommendations of the research is the necessity for financial analysts and investors to use artificial intelligence technologies because it contributes to the accuracy and speed of conducting analyses and comparisons that help improve the predictive value of information, as well as the necessity of employing and adopting big data analytics and capabilities due to the rapid and accurate data processing it provides. [ABSTRACT FROM AUTHOR]

The paper discusses the aspects of implementation of high-precision digital twins for power plants and energy systems based on the approaches used by General Electric (GE), which has an extensive experience in this field. To create such twins, the company uses laws of physics, knowledge and experience in engineering design, methods of measuring and controlling various parameters, as well as artificial intelligence technologies. The paper offers a description of models, methods, and approaches used by GE when developing digital twins. The company's experience in the use of artificial intelligence technologies, such as pattern recognition, unstructured (multimodal) data analysis, and expert networks, as well as sensor technologies is presented. The most important component of GE's digital twin is the Predix simulation platform. It was specifically developed by GE by using industrial Internet technologies to perform analytical processing of huge amounts of machine data in real time. The basic capabilities and specifications of the Predix platform are provided. [ABSTRACT FROM AUTHOR]

As digital technologies penetrate all spheres of human life, scientific and technological progress becomes a global development factor. Artificial intelligence (AI) is an advanced and rapidly developing area that has already proved its efficiency in healthcare, finance, and transport. However, AI also poses significant ethical and legal challenges because it can be used to generate and distribute virtual child pornography. The article features methods of generating virtual child pornography through various AI tools, their ethical implications, and the existing legal frameworks that cover these issues. In fact, the existing international and national laws on child abuse fail to take into account AI-generated images. The authors studied cases and legal precedents to highlight the urgent need for robust regulatory legal measures to prevent the misuse of AI technologies, the potential of which should be realized for the benefit of society.

Background. Artificial intelligence (AI) technologies hold significant promise for revolutionizing foreign language teaching methods. Current AI tools enable teachers to customize learning experiences, adapting materials and techniques to meet each learner's specific needs. By incorporating dynamic assessment into learning management systems, student progress is continually monitored, allowing educators to promptly adjust their teaching strategies. Immersive technologies, like virtual and augmented reality, offer interactive language environments where students can engage in real-life scenarios to practice their language skills. Speech synthesis technologies allow teachers to convert written text into spoken language, which improves students’ pronunciation and speaking skills. The purpose of the study is to examine the use of AI tools in teaching foreign languages at Russian universities and future trends in this area. Materials and methods. The authors analyzed current domestic and international scientific works on the integration of AI tools in foreign language education and conducted a study on the perception and evaluation of the aforementioned technology within the Russian teaching community. Results. A survey of 104 teachers showed the staff interest in mastering new technologies and their readiness to develop professional skills for the successful use of AI in the educational process. The study analyzes the current state of the field, identifies potential risks and discusses development prospects. The impact of AI on foreign language education tends to grow in the nearest future, opening up new opportunities for more effective and accessible learning.

Background. Cardiovascular diseases remain a pressing issue associated with great economic burden and loss of earning capacity. Among them, thoracic aortic aneurysms pose a serious threat as they commonly develop asymptomatically. Patients with aneurysms are often diagnosed late, which contributes to higher mortality rates due to complications. For this reason, conducting new epidemiological studies on this problem in our country is relevant.Objective: to study the prevalence of pathological dilatation of the thoracic aorta in Moscow by means of artificial intelligence technologies (AITs) using chest computed tomography (CT) data.Material and methods. A retrospective analysis of chest CT data from 227,149 patients obtained in the period from October 2022 to October 2023 was performed using AITs.Results. The analysis revealed that 13.3% of patients exhibited signs of thoracic aortic dilatation, while 0.8% had aneurysm signs. The prevalence of thoracic aortic aneurysms in Moscow was 12.4 cases per 100,000 individuals. Males were more susceptible than females; aneurysms of the descending aorta were more typical for them, while aneurysms of the ascending aorta were more common in females. The incidence of thoracic aortic dilatation increased with age. Potential causes and strategies to minimize AIT errors were discussed.Conclusion. The results highlight the importance of opportunistic screening for thoracic aortic aneurysms to ensure timely detection and prevention of complications. It would be especially beneficial to men and elderly population. The effectiveness of AITs to support decision-making by radiologists analyzing chest CT results was confirmed. The study provides an important update to the data on the prevalence of thoracic aortic aneurysms in asymptomatic patients in Russia. The identified features make it possible to direct the diagnostic and prevention efforts more effectively.

Purpose: to consider certain issues related to ensuring legal, economic and social development of Russia in the context of digital transformation and the use of artificial intelligence technologies, as well as some problems arising from the application of artificial intelligence technologies in public administration. The article considers legal problems related to the use of artificial intelligence technologies in the field of public administration. Research methods: the work is carried out using the methods of dialectics and system analysis, allowing for a comprehensive study of digitalization processes both at the federal level and at the level of the constituent entities of the Russian Federation, as well as within the unified system of public power. Results: the work highlights priority tasks for the formation of effective legal mechanisms to support and develop the data economy, including data collection and transmission, communication systems development, ensuring technological sovereignty of infrastructure for computing and data storage within the country (national cloud platforms, etc.), developing national standards and protocols for working with data, including those related to the use of artificial intelligence technologies. The paper substantiates their role in the development of multilateral relations in the transition to multipolarity, especially within the framework of regional associations, as well as systemic legal support for the tasks of scientific and technological development of the Russian Federation, based on the balance of national economic interests and the need to protect the rights, freedoms and legitimate interests of information systems users.

Digital technologies have removed all restrictions in the availability of information in a foreign language and deformed the motivation of students of non-language specialties to learn a foreign language. The authors believe that artificial intelligence technologies have the potential to systematically and purposefully influence students' motivation strategies. The goal of the research is to identify main directions of implementing artificial intelligence technologies in the language training process in the context of different motivation strategies. The research methods used are analysis of secondary data, systematization, synthesis, generalization. The research results are the following: 1) approaches to the development of motivational strategies have been differentiated and the prospects of introducing artificial intelligence technologies into the system of student motivation have been described; 2) the necessity of internalizing motives for learning a foreign language have been substantiated; 3) the priority directions of using artificial intelligence technologies in the process of forming students' motivational experience have been described. Key conclusions: 1) the main condition for the effectiveness of the foreign language teaching system is the formation of conditions for the internalization of learning motives; 2) the student's motivational experience is formed through the application of different motivational strategies and in accordance with the motivational design of the training course; 3) a teacher can use different approaches to the formation of the author's portfolio of motivational strategies; 4) artificial intelligence technologies allow to optimize and increase the effectiveness of the process of developing foreign language competences, but they are used in the following ways.

The article presents the results of scientific research on a comprehensive analysis of the problem of compliance with the principles of academic integrity in the context of active use of artificial intelligence tools in the educational and scientific activities of Ukraine and foreign countries. The author emphasizes that the modern vector of education declares the concept of academic integrity as a prerequisite for the formation of an effective system of education and science free from academic fraud and other types of related violations. It is established that the extremely rapid development of artificial intelligence technologies significantly affects all spheres of human activity, creating unique opportunities for learning and research, but at the same time giving rise to new ethical dilemmas. An analysis of the literature on this topic shows that global issues of using artificial intelligence in education and science are the subject of study and active discussion by many domestic and foreign scholars. At the same time, the peculiarities of observing and ensuring academic integrity by students, teachers and researchers in the context of preventing violations related to the misuse of artificial intelligence technologies re main insufficiently studied. The article analyzes the process of implementation of the provisions of international acts, in particular, the Magna Carta of Universities (1988) and the Bucharest Declaration of Ethical Values and Principles of European Higher Education (2004) into the national legislation of Ukraine, as well as the impact of the Bologna Process on the reform of the educational and scientific environment of our country. It is established that Ukraine's desire to comply with the generally recognized European principles of development of the education and science system places increased demands on the implementation of the concept of academic integrity in order to reduce the risks of violations in this area. The author emphasizes the need to adopt special legislation on academic integrity as soon as possible, given the relevance and importance of the issue under study. [ABSTRACT FROM AUTHOR]

Copyright of Central Asian Journal of Art Studies is the property of Central Asian Journal of Art Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research aims to study and analyze the role of adopting artificial intelligence technologies in supporting the predictive ability of financial statements in the context of big data. To achieve the research objective, the researchers designed a questionnaire that included three axes related to the research variables. It was distributed electronically to a sample of accountants, auditors, and investors in the Iraq Stock Exchange. Around 70 responses were collected from the sample members and relied upon in the practical aspect of the research. The SPSS statistical program was used to analyze the results. The research found that artificial intelligence technologies have a statistically significant effect in improving the predictive value of accounting information, and this effect increases in light of big data. Among the most important recommendations of the research is the necessity for financial analysts and investors to use artificial intelligence technologies because it contributes to the accuracy and speed of conducting analyses and comparisons that help improve the predictive value of information, as well as the necessity of employing and adopting big data analytics and capabilities due to the rapid and accurate data processing it provides.

The problem of the study lies in the identification of the role of Artificial Intelligence technologies in fostering creativity of radio and television production, as perceived by practicing journalists and experts. This encompasses creativity in both textual and visual aspects of the presented content, ultimately leading to increased effectiveness and audience engagement. The study is based on the theoretical frameworks of William Gordon's creative thinking theory, the creative components theory, and the media environment theory . The study employed a deliberate sampling method, surveying 125 individuals from the audience of journalists and experts in the field of radio and television production within media institutions. The study revealed that 96.8% of the sample relies on primary sources of innovative ideas to achieve distinctive television production on television channels. Additionally, 59.2% of the sample believes that these technologies contribute to the availability of professional media values, which Artificial Intelligence technologies help ensure in television messages. Moreover, 71.2% of the sample exhibited a high awareness of the advantages of Artificial Intelligence technologies. The study established a correlational relationship between the level of interest of communication managers in television channels and the utilization of Artificial Intelligence technologies in radio and television production, as well as the diversity of topics in which these technologies are employed. Furthermore, there was a correlational relationship between the sample's perception of professional media values which Artificial Intelligence technologies help ensure in television messages and the features of employing Artificial Intelligence technologies in radio and television production. The study also found a correlational relationship between the motivations of journalists to adopt creativity in the production of audience-oriented television content and the interests of television institutions in adopting innovative ideas and transforming them into tangible creative methods in the production of television and radio content. [ABSTRACT FROM AUTHOR]

This paper discusses the application of the Technology Development Envelope (TDE) as a road mapping tool in combination with the Delphi method and the Analytic Hierarchy Process (AHP). The method helps policy and decision-makers in organizations strategically manage emerging technologies by mapping their anticipated development path. The paper focused on creating a Technology Development Envelope (TDE) for artificial intelligence (AI) technologies in the food industry. In the first step, an expert panel identified a list of AI technologies applicable to the food industry. A hierarchical decision-making model, comprising 5 criteria and 24 sub-criteria for technology evaluation, was extracted from the literature and validated using the Delphi method. The Analytic Hierarchy Process (AHP) was used to determine the relative importance of criteria and subcriteria for evaluating the identified technologies. At this stage, the most important criteria considered were food safety and social and political acceptance of the technology. The expected value of each technology was calculated over different periods, resulting in the development of the Technology Development Evaluation (TDE) for AI technologies in the food industry within a ten-year horizon. The analysis of the future indicates that technologies such as computer vision, robotics, industrial automation, and machine learning will undergo continuous improvements over time and eventually become dominant technologies in the food industry. These advancements can lead to an increase in quality and efficiency within the food industry. Finally, sensitivity analysis was conducted to test the model’s sensitivity and explore how policymakers’ extreme strategies affect the model’s outputs. [ABSTRACT FROM AUTHOR]

AI is analysed from different perspectives, one of which is the application of AI in the public sector. The development of the AI requires a responsible approach, including ethical guidelines, regulation, and continuous public education. It is important to strike a balance between promoting innovation and minimising potential negative consequences. There is also a need to promote technology development in a way that benefits society as a whole and not just certain groups. It is becoming a common tool in education. Already, AI is changing the way schools, universities, students, and educators work and children learn. Educational institutions benefit from it by helping teachers meet the specific needs of each learner. There is a strong push for closer cooperation on digital education at European Union level and the importance of collaboration across all sectors to make education fit for the digital age. The article provides a general overview of artificial intelligence, its impact on society, how it can be applied in the public sector, whether humans are already able to exploit and benefit from this technology, and how to guard against the negative effects of technology. What legal measures need to be taken to ensure that artificial intelligence is a progress for mankind and not a regression in any field.

Green buildings are designed and constructed according to the principles of sustainable development and are an inevitable trend in future architectural development. Nowadays, many works have studied the application of intelligence or intelligent technology in green intelligent buildings, but there is still insufficient discussion on how to integrate intelligent technology into all aspects of buildings. In view of this, this paper summarizes the design concepts of modern green buildings and takes this as the starting point to explore the classification and construction of the core needs for achieving sustainable development throughout the life cycle of buildings from five aspects: building design, building materials, building construction, building renewal and management, and building damage, and analyze the integration of relevant intelligent technologies in buildings under different needs.

During times of crisis, like in healthcare emergencies or disruptions in logistics and supply chains, decision-makers encounter significant challenges in managing resources efficiently. This study proposes an approach combining different information types and advanced computer techniques to improve how we handle crises. By looking at data connected with blockchain technology, we aim to understand crises better and help people make smarter decisions. We use a special kind of computer model called Long Short-Term Memory (LSTM) to guess what might happen during a crisis, like how many people might get sick or if there might be problems with getting supplies. Our model is right about 87% of the time. To understand why the computer makes these guesses, we use a method called SHapley Additive exPlanations (SHAP), which is widely known. However, we notice that SHAP sometimes doesn’t explain things well for the entire period we’re looking at. So, we suggest some changes to the SHAP method to explain things better for smaller parts of time. These changes help the method explain things better for small bits of time, but it might not be as good at explaining everything overall. To ensure our idea works, we compare our computer model’s guesses and explanations with those from other models that look at data differently. We show the good and bad parts of our method in different crises.

This paper discusses the application of the technology development envelop (TDE) as a road mapping tool in combination with Delphi method and Analytic Hierarchy Process (AHP). The method aids policy and decision makers in organizations to strategically manage emerging technologies by mapping their anticipated development path. The paper focused on creating a Technology Development Envelope (TDE) for artificial intelligence (AI) technologies in the food industry. At first step a list of AI technologies applicable to the food industry was identified through an expert panel. A hierarchical decision-making model, consisting of 5 criteria and 24 sub-criteria for technology evaluation, was extracted from literature and verified through the Delphi method. The AHP was used to determine the relative importance of criteria and sub-criteria for evaluating the identified technologies. At this step, food safety and social and political acceptance of technology were considered as the most important criteria. Then the expected value of each technology was then calculated over different time periods, resulting in the development of the TDE for AI technologies in the food industry within a ten-year horizon. The analysis of the future indicates that technologies such as computer vision, robotics, industrial automation, and machine learning will undergo improvements over time and eventually transform into dominant technologies in the food industry. These advancements can lead to an increase in quality and efficiency within the food industry. Finally sensitivity analysis was conducted to test the model's sensitivity and explore how policy makers' extreme strategies affects the model's outputs.

The biomedical literature is a vast and invaluable resource for biomedical research. Integrating knowledge from the literature with biomedical data can help biological studies and the clinical decision-making process. Efforts have been made to gather information from the biomedical literature and create biomedical knowledge bases, such as KEGG and Reactome. However, manual curation remains the primary method to retrieve accurate biomedical entities and relationships. Manual curation becomes increasingly challenging and costly as the volume of biomedical publications quickly grows. Fortunately, recent advancements in Artificial Intelligence (AI) technologies offer the potential to automate the process of curating, updating, and integrating knowledge from the literature. Herein, we highlight the AI capabilities to aid in mining knowledge and building the knowledge base from the biomedical literature.

The subject of the article is the management of artificial intelligence in the field of higher education, which improves the quality of knowledge and reduces the risks of learning in the context of digitalization. The purpose of the article is to identify the problems hindering the development of artificial intelligence in higher education and to develop recommendations for their solution. The research methodology is based on the use of modern methods, techniques and tools in the study of artificial intelligence, allowing to take into account the impact on the education quality, on the psychology participants in the educational process and on the mechanisms for managing its development. The main results obtained in the article provide answers to ambiguous questions about the feasibility of large-scale use of artificial intelligence in education, its dominance among other methods of knowledge transfer and its application in its pure form, without live communication with teachers. The answers received in the article convince the opponents of this topic that the use of the author’s developments regulating the use of artificial intelligence in education leads to an increase in the quality of education and neutralizing the emerging risks of learning from a new generation. The article reveals ethical shortcomings and shows the advantages of the artificial intelligence technologies use in the practice of tertiary education. The main conclusions made in the article are based on the statement that the artificial intelligence system in the field of tertiary education needs to be regulated and managed by development using the methods of psychological, organizational, regulatory and technological character proposed by the authors.

Currently, in the air defense system of units of the national security and defense sector of Ukraine, despite the constant updating (replenishment) of the park with modern models, there are still shortcomings in the system of detecting air targets of the surface layer with a small and ultra-small effective scattering surface. One of the most effective and cost-effective, from the point of view of financial and time resources, approaches is the creation of a modern tactical level information platform. Such a platform is based on the use of passive (seismic, acoustic, optical-electronic, magnetic, infrared, and other) sensors in military radio network structures compatible with the geographic information system (GIS) to identify targets of the surface layer that pose threats to military and infrastructure facilities of Ukraine. This article is dedicated to a thorough analysis of the routing management algorithm in sensor radio networks, with a focus on enhancing their stability and reliability. The authors concentrate on challenges associated with complex network operating conditions, such as instability of network interfaces, equipment failures, and various external and internal interferences that can negatively impact network performance. Special attention is given to the use of Gaussian Mixture Models (GMM) for modeling multimodal data, which allows for increased accuracy and efficiency in routing management. The results presented in the article demonstrate that the proposed algorithm has high accuracy, as confirmed by comparison with data obtained through simulation modeling. This indicates the practical applicability of the algorithm in real-world conditions. The research opens new perspectives for improving the stability and reliability of sensor radio networks, which is particularly relevant in the context of widespread use of wireless technologies. The proposed algorithm can be used to develop more reliable and efficient routing management systems, ensuring better adaptation to the changing conditions and challenges faced by modern wireless networks. [ABSTRACT FROM AUTHOR]

Copyright of Arab International Journal of Knowledge Management is the property of Arab Institution of Knowledge Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Prostheses play an important role in the rehabilitation of people who have suffered some type of amputation. However, due to its high‐cost and high complexity in performing movements of everyday tasks, users of these prostheses may encounter many difficulties. Therefore, this work proposes the development of a future artificial intelligence technology based on a low‐cost functional prosthesis prototype (manufactured in a 3D printer). In the present work, we describe an intelligent system that uses an artificial neural network to recognize patterns in muscle biopotential signals in order to control a prosthesis prototype in real time. Such a system is divided into three parts: the first that performs a human–machine integration through a graphical user interface; the second that performs the signal acquisition; the third that performs the training and generalization steps of the artificial neural network. The developed interface runs on a web application that has a database hosted in the cloud and in it the system user can: Acquisition of electromyography signals; Training phase of the artificial neural network; Sends the matrix of weights of the trained network to the microcontroller; Activates in the microcontroller, the state of action of the commands from the identified gestures. To compose the results of the present work, a search was initially carried out for the ideal parameters of the artificial neural network through signals obtained from 20 volunteers. In this step, it was possible to identify the topology that best classifies the signals of each gesture, as well as the investigation of the number of neurons in the hidden layer that causes a low generalization power due to overfitting. At the end of the project, it was possible to validate the use of the system with 15 new volunteers, and it was observed that in most cases, the performance of the commands in the prosthesis prototype were performed correctly. In addition, a project cost analysis was carried out, and it was possible to verify that the prototype developed is viable and has an affordable cost in relation to the Brazilian cost of living standards. In this way, the objective of the present work is in the development of a low cost artificial intelligence technology. Such a system is equipped with an algorithm based on neural networks that can deal with different muscle biopotential signals, in order to command a robotic prosthesis. [ABSTRACT FROM AUTHOR]

Over the last few years, the global academic community has been wondering about the possibility and efficiency of using artificial intelligence technologies in the educational process in general, and in the process of teaching foreign languages in particular. Among the theorists and practitioners in the field of education there appeared both ardent supporters of the use of these technologies, and strong opponents of this idea. Our experimental study proved the efficiency of artificial intelligence technologies in the process of the formation of foreign language communicative competence of students of non-linguistic specialties of higher educational institutions. At the same time, we emphasize that the role of the teacher in the process of organizing the educational process remains fundamental, whereas his/her additional tasks in modern conditions include a careful selection of artificial intelligence technologies, creation of a set of exercises based on their application, which should contribute to the formation of professional competencies of students. [ABSTRACT FROM AUTHOR]

In recent years, artificial intelligence has started to play an important role in digital marketing. Companies are increasingly using this technology to personalize content, improve the performance of marketing campaigns and user experience. According to a Google report published in 2021, Romania is one of the leading countries in Central and Eastern Europe in terms of significant growth in digital advertising expenditure. As a result, the current research aims to assess the importance and impact of AI usage in Romanian companies that activate in digital marketing. To conduct this study, an online survey was developed consisting of 11 questions to establish the utilization of AI in digital marketing and the perception of employees in companies towards this technology. The sample group was selected from a contact list of digital marketing firms, social media, and professional groups. Out of the total of 30 responses collected, valid data was analyzed to identify emerging trends and patterns in the use of AI in digital marketing. The survey findings indicate that AI is perceived as a valuable tool for enhancing user experience and increasing the effectiveness of digital marketing campaigns. It is important to consider the ethical and confidentiality implications when utilizing customer data, and to refrain from employing AI in a harmful or intrusive manner. [ABSTRACT FROM AUTHOR]

The basic mission of the Artificial Intelligence Research Center of the HSE University (AI Center) is the development of artificial intelligence (AI) technologies and their implementation in various spheres of human and society life, science branches, and economy sectors. At the AI Center, new AI technologies expanding the field of AI applications are developed, software tools for AI application in science and business are created, and an open software library of AI methods for solving tasks of high social importance is developed. [ABSTRACT FROM AUTHOR]

The optimization of processes associated with artificial insemination (AI) is of great importance for the success of the pig industry. Over the last two decades, great reproductive performance has been achieved, making further significant progress limited. Optimizing the AI program, however, is essential to the pig industry's sustainability. Thus, the aim is not only to reduce the number of sperm cells used per estrous sow but also to improve some practical management in sow farms and boar studs to transform the high reproductive performance to a more efficient program. As productivity is mainly influenced by the number of inseminated sows, guaranteeing a constant breeding group and with healthy animals is paramount. In the AI studs, all management must ensure conditions to the health of the boars. Some strategies have been proposed and discussed to achieve these targets. A constant flow of high-quality and well-managed breeding groups, quality control of semen doses produced, more reliable technology in the laboratory routine, removal of less fertile boars, the use of intrauterine AI, the use of a single AI with control of estrus and ovulation (fixed-time AI), estrus detection based on artificial intelligence technologies, and optimization regarding the use of semen doses from high genetic-indexed boars are some strategies in which improvement is sought. In addition to these new approaches, we must revisit the processes used in boar studs, semen delivery network, and sow farm management for a more efficient AI program. This review discusses the challenges and opportunities in adopting some technologies to achieve satisfactory reproductive performance and efficiency. • Herd productivity is achieved by ensuring a constant flow of inseminated sows. • Good management of gilts and weaned sows is paramount for fertility success. • Quality control processes in semen dose production are fundamental to AI success. • Sperm cells used can be reduced in dose and/or by optimizing the insemination number. • Sperm output is maximized with management, good nutrition, and facilities. [ABSTRACT FROM AUTHOR]

The article provides insight into how developments in artificial intelligence (AI) affect the balance of power in the digital world order. This study reveals the global trends in the political and regulatory support for the development and implementation of AI, as well as peculiarities of government strategies in this area.The United States of America and China have been proven to be the most powerful actors in the international system in using AI. Thanks to investments, regulatory and institutional support and the introduction of AI technologies in the foreign policy’s domain, these two states form a duopoly of the digital world order. A significant advantage of the United States and China in promoting artificial intelligence is the presence of transnational tech giants such as Google and Tencent, etc. It is noted that European countries, primarily those that are part of the EU, are united by an ethical-oriented approach to the production and implementation of AI technologies. However, they are inferior to the United States and China in investment and infrastructure support for the development of artificial intelligence technologies. Our findings indicate that access to data is a challenge for states claiming technological dominance in the international system. In this aspect, the advantage is on the side of China. The latter not only has full-scale access to the personal data of its citizens, but is also actively developing tools for collecting data in other states, in particular by implementing the «Digital Silk Road» strategy. The paper highlights the correlations between the introduction of new technologies and the reconfiguration of the geopolitical balance of forces in the historical retrospective. Our analysis confirms that a feature of the current stage of technological development is that the primacy in the implementation of AI technologies provides an advantage only in the short term. Unlike previous technological revolutions, the current one is characterized by the rapidity of adaptation and the comprehensive implementation of AI, and thus provides an opportunity for any actor in international relations, public or private to make systemic impact, which can dramatically change the geopolitical balance of power on the international stage.

The purpose of the research is to summarize the experience and outline the prospects for the application of artificial intelligence technologies in the film industry. The research methodology is based on the application of general scientific methods of analysis and synthesis, which made it possible to properly analyze the subject of research. The scientific novelty of the results obtained is to generalize the experience and outline the prospects for the use of artificial intelligence technologies in the film industry. Conclusions. It is emphasized that AI technologies in the cultural and artistic sphere not only complement the process of producing artistic works but also can significantly change the entire industry, which raises debates about the likelihood of biased and uniform AI decisions, as well as the fact that AI does not take into account cultural shifts and changes in trends that will occur in the future, etc. In the future, the degree of AI involvement in creative processes will only increase. The more AI technologies are used in the creative process, the more the value of ideas and concepts increases – it is new ideas that will determine the nature of art development. It was emphasized that numerous controversial issues of the use of artificial intelligence technologies in the film industry have yet to be explored. In particular, not only the impact of AI technologies on the film production process but also the tendency in cinema to change the attitude of society to potential threats associated with artificial intelligence requires further study. Society is beginning to realize the need not only for “useful cooperation” between technology and humanity but also for society to develop priorities for the use of technology, including focusing on social values, empowerment, contributing to shaping the future by and for people, etc. This requires responsible management of technologies, control over their use, and justification of the optimal implementation of values in their development.

The power industry is at a point of intersection. Modern technical advances have the potential to drastically alter our electricity supply, trading, and usage. Artificial intelligence (AI) technologies are transforming the current modernization approach. Big data management, vast computational resources, telecommunications, enhanced machine learning, and deep learning techniques have all contributed to the rapid surge in AI technology. Smooth software that improves judgment and management will automatically adjust the merging of electricity supply, usage, and sustainable energy into the electricity network. Supercomputers, power systems, and communications networks between the command center and devices are all part of a smart electricity system. AI is expected to be crucial in attaining the abovementioned capabilities. This research assessed whether artificial intelligence algorithms surpass conventional methods in stability, massive data management, smart grid, energy-saving optimization, and planned maintenance management for renewables. Based on recent findings, it can be concluded that AI will play an essential part in the future energy industry. To obtain better results, the sustainable energy industry, companies, power network administrators, and independent generators of electricity should place more emphasis on AI technologies. [ABSTRACT FROM AUTHOR]

The insertion of artificial intelligence technologies (AITs) and data-driven automation in public policymaking should be a metaphorical wake-up call for critical policy analysts. Both its wide representation as techno-solutionist remedy in otherwise slow, inefficient, and biased public decision-making and its regulation as a matter of rational risk analysis are conceptually flawed and democratically problematic. To 'outsmart' AI, this article stimulates the articulation of a critical research agenda on AITs and public policy, outlining three interconnected lines of inquiry for future research: (1) interpretivist disclosure of the norms and values that shape perceptions and uses of AITs in public policy, (2) exploration of AITs in public policy as a contingent practice of complex human-machine interactions, and (3) emancipatory critique of how 'smart' governance projects and AIT regulation interact with (global) inequalities and power relations. [ABSTRACT FROM AUTHOR]

The power industry is at a point of intersection. Modern technical advances have the potential to drastically alter our electricity supply, trading, and usage. Artificial intelligence (AI) technologies are transforming the current modernization approach. Big data management, vast computational resources, telecommunications, enhanced machine learning, and deep learning techniques have all contributed to the rapid surge in AI technology. Smooth software that improves judgment and management will automatically adjust the merging of electricity supply, usage, and sustainable energy into the electricity network. Supercomputers, power systems, and communications networks between the command center and devices are all part of a smart electricity system. AI is expected to be crucial in attaining the abovementioned capabilities. This research assessed whether artificial intelligence algorithms surpass conventional methods in stability, massive data management, smart grid, energy-saving optimization, and planned maintenance management for renewables. Based on recent findings, it can be concluded that AI will play an essential part in the future energy industry. To obtain better results, the sustainable energy industry, companies, power network administrators, and independent generators of electricity should place more emphasis on AI technologies.

This paper explores how the robotic process automation (RPA) can benefit financial applications. To fully exploit RPA technologies potential will empower higher education and finance, which makes a better future together. The mechanism of RPA to mimic the process of human thinking in solving financial problems was discussed. Important technologies, challenges from cooperativeness, responsiveness and interconnectedness were explored. Exploration of automation technologies for COVID-19 prevention will reduce virus transmission, which empowers society governance, higher education and finance. [ABSTRACT FROM AUTHOR]

The article considers peculiarities of the activities of the main participants in the financial market, in particular banking in the context of digitalization and the introduction of artificial intelligence tools. At present, artificial intelligence (AI) technologies have a significant impact on human life, both in the process of instant transfers and in conversational interfaces. This affects the financial services sector, and its members are the most active in introducing disruptive AI innovations. Therefore, in order to increase the level of competitiveness, modern banks should act as locomotives in addressing issues of implementation, use of digital technologies and acceleration of methods of remote work. The COVID-19 pandemic has made its own adjustments to the concept of interaction of financial institutions with customers, for most of whom remote services have become an integral part of everyday life. The increasing demand for telecommuting services of financial institutions stimulates the creation of digital platforms that take into account both the processes of global digitalization and the changed demands of consumers in the context of a pandemic. This article provides an analytical overview of trends, obstacles and prospects for the integration of financial ecosystems and marketplaces in the Russian market. The necessity of using an integrated approach in developing the rules for the functioning of financial ecosystems in the formation of an adequate development strategy, which will ensure the creation of a fair competitive environment in the financial market, has been substantiated. The aim of the research is to identify the main trends and patterns in the financial services market, as well as to determine the vector for further development of financial ecosystems formed using artificial intelligence tools. To achieve this goal such general scientific methods as theoretical generalization, analysis and synthesis, comparative analysis, systems approach, etc. have been used.

We can already say with certainty, that the basis for the development of modern electric power industry will soon be intellectual, digital transformation of production assets, which in itself opens a new approach to the problem of increasing operational efficiency and labor productivity. The main difficulty in this way is, that the existing research of digital technologies do not take into account the applied aspects of the implementation of its products according to the industry specifics and business goals of companies – market entities. In this paper, the analysis and classification of commercial IT products have been made by subject groups of solutions, that meet the needs of specific target areas of activity of electric power companies. The conceptual description of the subject groups of digital solutions on the basis of known examples and practices of their application has been adduced.