Earticle

Island tourism offers distinct attractions compared to land-based travel, providing visitors with unique natural environments and independent cultures not found on the mainland. Due to its ability to facilitate various leisure activities and provide an escape from daily routines, island tourism is expected to maintain steady demand. However, it is also more vulnerable to change in climate and weather changes, making it susceptible to significant restrictions and direct impacts. Despite the growing interest in island tourism, existing research has primarily focused on island classification rather than strategies for effectively utilizing island tourism resources. This study aims to develop a data-driven evaluation and activation strategy for island tourism resources in Jeollanam-do, South Korea. To achieve this, an island classification system is proposed to systematically categorize islands based on their tourism-related characteristics. The classification system is constructed using exploratory factor analysis and a clustering technique based on the Gaussian Mixture Model (GMM), allowing for the identification of key island attributes. Furthermore, an island recommendation algorithm is introduced based on the established classification system, providing strategic insights for the efficient management and promotion of island tourism resources. The findings of this study contribute to enhancing the sustainable utilization of island tourism by offering a systematic framework for resource evaluation and strategic development.

Birth rates are shaped by a complex interplay of socioeconomic and environmental factors, yet the extent to which air pollution and climatic variability influence birth rates remains an understudied area in Mongolia. This study investigates the impact of air pollution, environmental conditions, and economic factors on birth rates in Mongolia from 2016 to 2024. While economic conditions have traditionally been regarded as the primary determinants of birth trends, recent evidence suggests that environmental factors such as air pollution and climatic variability may also play a crucial role. This study employs multiple regression techniques, including linear regression, ridge regression, lasso regression, and elastic net regression, to identify the most predictive model for birth rate fluctuations. The findings indicate that incorporating environmental variables significantly enhances model performance, as demonstrated through linear regression and ANOVA comparisons between economic-only and full models. Among the models, lasso regression exhibits the best fit, demonstrating superior predictive accuracy in estimating birth rates. The results highlight the strong negative influence of economic instability—particularly mortgage loan burdens— on fertility trends, while also underscoring the substantial impact of air pollution and climatic factors. These findings suggest that an integrated approach addressing both economic and environmental determinants is necessary for effective policy interventions aimed at improving reproductive health outcomes in Mongolia.

Web3 Internet structure has been widely investigated to support data sovereignty of individuals. In order to protect privacy of individuals, sensitive information within personal data needs to be hidden before disclosing it outside. One method hiding the sensitive information such as phone number and resident registration number is pseudonymization technology, which converts the sensitive information into a non-interpretable identifier. To connect securely the non-interpretable identifier to its data owner, the previous central system employs a single computer that stores the mapping table between the non-interpretable identifier and the connecting address of its owner. Because the previous system is vulnerable to internal and external attacks, this paper proposes a distributed system, in which multiple computers divide up the roles to perform the mapping. Evaluation verifies that the proposed system is robust against external and internal attacks. Although the execution time of the proposed systems is longer than that of the previous system, its difference is negligible.

The purpose of this study is to gain an in-depth understanding of the meaningful life experiences of middle-aged women and comprehensively examine the results of those experiences by systematically comparing, analyzing, interpreting, and synthesizing qualitative research results that explore middle-aged women’s life experiences including menopause, climacteric, and aging. Meta-ethnography proposed by Noblit and Hare was used for qualitative meta-synthesis. The literature was searched in domestic databases: DataBase Periodical Information Academic (DBpia), Research Information Sharing Service (RISS), ScienceON, National Assembly Digital Library, Korean studies Information Service System (KISS), and Korea Citation Index (KCI). Search terms included ‘middle-aged women,’ ‘life,’ ‘menopause,’ ‘menopause symptoms,’ ‘climacteric,’ ‘aging,’ ‘change,’ ‘perception,’ and ‘adaptation.’ Finally, 13 qualitative studies were analyzed and synthesized. The central experience of Korean middle-aged women’s lives was ‘internal growth and reinterpretation of the meanings of life’, and four themes were derived: ‘understanding of and active responses to physical changes’, ‘acceptance of and internal reflection on emotional changes and active responses to them’, ‘reestablishment of interpersonal relationships with important people centered on family and efforts to adapt to changed relationships’, and ‘reestablishment of self-identity and taking control of life’. The significance of this study is that it reveals that middle-aged women view the changes and challenges in various aspects of life they face in middle age as opportunities for internal growth, discover new meaning and value, and lead their own lives proactively.