http://repository.enu.kz/handle/enu/16981 Fri, 03 Apr 2026 21:57:35 GMT 2026-04-03T21:57:35Z http://repository.enu.kz/handle/enu/29227 Public management of scientists’ potential as a source of economic development: A bibliometric analysis Kangalakova, Dana; Satpayeva, Zaira; Nurkenova, Makpal; Suleimenova, Arailym Particular hopes have always been placed on the potential of scientists because they can act as a driving force for effective government. Understanding the importance of scientists ensured progress and prosperity for leading civilizations. This study aims to identify an evolutionary-chronological, geographical, and contextual scientific landscape of the development and management of the potential of scientists through a comprehensive bibliometric analysis. Initially, 5619 publications in the Scopus database were selected from 1957 to 2023. The evolution of knowledge about the importance of public administration of scientific personnel began in 1957 and reached its peak in 2019. Authors from the USA, Great Britain, and Australia have published more about the significance of managing the potential of scientific personnel, and strong schools of knowledge about scientific personnel are concentrated in the USA, France, Canada, and Australia. The analysis of the research’s conceptual orientation shows that publications in environmental and social sciences dominate this sphere. In addition, the bibliometric analysis results show that public management of scientific personnel will bring benefits such as effective government policy decisions, increased innovation activity, commercialization, and improvement of the population’s social life. The results of this study lay the foundation for future research that should improve the management of scientific personnel’s potential. Mon, 01 Jan 2024 00:00:00 GMT http://repository.enu.kz/handle/enu/29227 2024-01-01T00:00:00Z http://repository.enu.kz/handle/enu/29226 Network Attack Detection Using NeuroEvolution of Augmenting Topologies (NEAT) Algorithm Zhukabayeva, Tamara; Adamova, Aigul; Ven-Tsen, Khu; Nurlan, Zhanserik; Mardenov, Yerik; Karabayev, Nurdaulet The imperfection of existing intrusion detection methods and the changing nature of malicious actions on the attacker's part led to the Internet of Things (IoT) network interaction in an unsafe state. The actual problem of improving the technology of the IOT is counteracting malicious network impacts. In this regard, research and development aimed at creating effective tools for solving applied problems within the framework of this problem are becoming increasingly important. This study seeks to develop tools for detecting anomalous network conditions resulting from malicious attacks. In particular, the accuracy of the identification of DoS and DDoS attacks is sufficient for operational use. This study analyzes various multi-level architectures, relevant communication protocols, and different types of network attacks. The presented research was conducted on open datasets TON_IOT DATASETS, which include multiple data sources collected from IoT sensors. The modified HyperNEAT algorithm was used as the basis for the development. The NEAT methodology used in the study allows you to combine various network nodes. Results of the study: a neuro-evolutionary algorithm for identifying DoS and DDoS attacks was implemented, integrated, and real-tested based on a multi-level analysis of network traffic combined with various adaptive modules. The accuracy of identifying DoS and DDoS attacks is 0.9242 in the Accuracy metric. The study implies that the proposed approach can be recommended for network intrusion detection, ensuring security when interacting with the IoT. Mon, 01 Jan 2024 00:00:00 GMT http://repository.enu.kz/handle/enu/29226 2024-01-01T00:00:00Z http://repository.enu.kz/handle/enu/29225 Interconnections in the education–migration–labor market chain in Central and Eastern Europe Mukhtarova, Naila; Nurtazina, Roza; Krawczyk, Dariusz; Barvinok, Veronika; Vorontsova, Anna; Vasić, Sergej; Vasylieva, Tetiana This study examines the interconnections between transformations in the education sphere, migrations waves, and labor market in 2000–2021 based on a panel data set for 14 Central and Eastern European countries (7 – former members of the Council for Mutual Economic Assistance; 5 – former republics of the USSR, and 2 – former republics of Yugoslavia). Statistical data were collected from the World Bank, the Organisation for Economic Cooperation and Development, and the International Labour Organization databases. To describe this interconnection, a pool of parameters was formed. Those that cause the greatest variability were selected using exploratory factor analysis: for education – the number of teachers and students in higher education and public spending on education; for migration – the net migration flow, personal remittances sent and received; for labor market – unemployment rate and the share of highly educated people among the employed. Confirmatory factor analysis identified the most influential determinants: for education – the number of students in higher education; for migration – paid personal remittances; for labor market – unemployment rate. The covariance analysis demonstrated a robust direct correlation between education and migration (positive shifts in the education sector serve as a catalyst for pursuing superior employment opportunities or continuing education abroad). A relatively weak direct correlation was between education and the labor market (a more highly educated workforce has only a limited impact on the structure and dynamics of the labor market). Finally, a moderate inverse correlation was between migration and the labor market (deteriorating labor market conditions give rise to migration waves). Mon, 01 Jan 2024 00:00:00 GMT http://repository.enu.kz/handle/enu/29225 2024-01-01T00:00:00Z http://repository.enu.kz/handle/enu/29224 Improving the practical competence of students through educational and market cooperation Bilyk, Liubov; Murzagaliev, Erdos; Skibina, Olena; Hryn, Olga; Kravchenko, Tamara Introduction: the relevance of cooperation between educational institutions and employers in developing students’ practical competence has gained prominence, supported by theories such as the dual education model and competence-based approaches. However, a significant gap remains concerning the practical relevance of education provided to students. Method: this study adopted a qualitative methodology, employing the PRISMA approach for systematic literature review. Literature selection adhered to five strict inclusion criteria, limiting the review to Englishlanguage publications dated between 2019 and 2024. Ultimately, 36 sources were identified and analyzed. Results: the analysis revealed a persistent problem of insufficient practical training relevance within modern education systems. Commonly utilized practices included implementing dual education models and engaging employers in curriculum development and teaching roles. Conversely, the establishment and functioning of career centers were less frequently highlighted in existing literature, despite evidence demonstrating their significant role in developing specific practical skills. Conclusions: the findings underscored the critical importance of collaboration between educational institutions and employers for enhancing students’ practical competence. Dual education and employer involvement emerged as prevalent practices, yet career centers require greater attention due to their potential for skill development. The study was limited by its exclusive focus on English-language sources and the stringent criteria inherent to the PRISMA methodology. Nevertheless, the research contributes valuable insights by systematically addressing the diverse mechanisms through which educational-employer cooperation positively impacts student competence development. Wed, 01 Jan 2025 00:00:00 GMT http://repository.enu.kz/handle/enu/29224 2025-01-01T00:00:00Z