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Topics in Linguistics (2025), 26(1), pp. 92−118 10.17846/topling-2025-0005 The development of research competence in postgraduate foreign language students using project-based methods
This article is aimed at evaluating the effectiveness of developing research competence in postgraduate foreign language students, enhancing their scientific and research skills, enabling independent problem-solving in their professional field, and improving their academic training through project-based methods. Today’s educational paradigm puts students themselves at the centre of the educational process, their needs, characteristics and talents and their development; the need for a teacher to master research competence is obvious. One of the most effective ways to form specialists with creative thinking is to involve postgraduate foreign language students in research activities. With research competence, a specialist is able to actively and productively analyse evidence, and develop and apply new, more efficient algorithms, resources and technologies, instead of being limited to using ready-made, sometimes outdated solutions. The authors of this study highlight that while postgraduate foreign language students understand the concept, goals, and objectives of research, they often lack the motivation and skills required for independent work, information analysis, and research competence development. To address this challenge, research competence must be systematically cultivated from the early stages of postgraduate education.
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Load Balancing in DCN Servers Through Software Defined Network Machine Learning
In this research paper, we delve into the innovative realm of optimizing load balancing in Data Center Networks (DCNs) by leveraging the capabilities of Software-Defined Networking (SDN) and machine learning algorithms.
Traditional DCN architectures face significant challenges in handling unpredictable traffic patterns, leading to bottlenecks, network congestion, and suboptimal utilization of resources. Our study proposes a novel framework that integrates the flexibility and programmability of SDN with the predictive and analytical prowess of machine learning.


