June 30 · Article · Bulletin of D Serikbayev EKTU · Artificial Intelligence
The article presents a comparative analysis of LSTM and BERT models applied to multi- classification tasks in the Kazakh language using a named entity recognition dataset. The study primarily focuses on addressing the issue of limited resources for processing Kazakh text by adapting existing machine learning methods for the analysis of multidimensional classification tasks. Both approaches have demonstrated their effectiveness in various aspects of text data processing, including modeling contextual dependencies and accurately classifying multiple categories. The LSTM model exhibited a high capability for capturing temporal dependencies in text, making it suitable for classification tasks in low-resource language settings. Meanwhile, the BERT model, based on the Transformer architecture, showed superior results in contextual analysis and processing of complex text structures, ensuring higher performance in multi-classification of Kazakh text. The experimental results indicate that both models can be effectively employed for text classification tasks in the Kazakh language. However, the BERT model demonstrated more stable and reliable outcomes, attributed to its ability for deeper contextual understanding. The findings underscore the importance of applying modern natural language processing (NLP) methods to low-resource languages and open new avenues for further research and practical application
OMOrken MamyrbayevOpen access
June 30 · Article · Bulletin of the International University of Tourism and Hospitality. · Tourism, Leisure and Hospitality Management
This study examines the long-term relationship and causality direction between tourism revenues and economic growth in developing countries. In this context, annual data from eight countries, namely Brazil, Cuba, Georgia, Malaysia, Mexico, South Africa, Thailand and Turkey, between the years 2000-2023 were used. Within the scope of the analysis, Pedroni and Kao cointegration tests were applied to determine the long-term cointegration relationship. In addition, Dumitrescu and Hurlin panel causality test was used to determine the causality direction between the variables. The findings show that there is a long-term cointegration relationship between tourism revenues and economic growth in developing countries. The causality analysis results reveal that there is a unidirectional causality relationship from tourism revenues to economic growth. This finding shows that the tourism sector makes a significant contribution to the economic growth of the examined countries and that tourism should be considered as a strategic sector in terms of sustainable development policies. The study emphasizes the role of tourism on economic growth in developing countries and provides important information to policy makers and investors. The results obtained show that incentives for the tourism sector can support economic growth and draw attention to the necessity of sustainable tourism policies. In this context, supporting tourism with infrastructure investments, promotional activities and sustainable development strategies stands out as a critical factor in terms of economic growth.
GAGulmira AzretbergenovaOpen access
June 30 · Article · BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS · Numerical Analysis
The article focuses on the initial problem for a third-order linear integro-differential equation with a small parameter at the higher derivatives, assuming that the roots of the additional characteristic equation have opposite signs. This paper presents a fundamental set of solutions and initial functions for a singularly perturbed homogeneous differential equation. The solution to the singularly perturbed initial integrodifferential problem employs analytical formulas. A theorem concerning asymptotic estimates of the solution is established.
AMAziza MirzakulovaOpen access
