Earticle

This study aims to propose strategic improvements to Korea's public grain stockpiling policy to enhance food security, focusing on critical infrastructure elements. In light of the COVID-19 pandemic and the disruption of global grain supply chains, exacerbated by major events such as Russia’s invasion of Ukraine, food security has gained heightened global importance. Korea, facing similar challenges, requires a fundamental national strategy to safeguard its food supply. The government has initiated several public grain stockpiling policies, including the Mid-to-Long-Term Food Security Reinforcement Plan. This study evaluates these policies by analyzing three key aspects of critical infrastructure— function, facility, and system. Based on the analysis, the study identifies essential tasks for the Korean government: 1) fostering public-private cooperation by providing specific incentives for private sector involvement, rather than relying solely on voluntary participation; 2) designating public grain stockpiling facilities as critical infrastructure and ensuring their systematic management; and 3) establishing clear operational guidelines within the existing legal framework to effectively meet stockpiling goals and manage the system.

This study examines communication strategies during animal disease crises, focusing on avian influenza, African swine fever, foot-and-mouth disease, and COVID-19 in South Korea. Data were gathered from 530 veterinarians and farm owners via surveys and interviews, using a mixed-methods approach to evaluate communication effectiveness. Four critical components—promptness, accuracy, transparency, and interactivity—were found to significantly influence crisis response. Quantitative analysis showed strong correlations between these factors and improved management, while qualitative data highlighted issues with consistency and guideline ambiguity. Media outlets were analyzed for their role in disseminating veterinary information. Recommendations include creating an integrated communication platform, stakeholder training, and transparent information sharing to enhance trust and crisis management. The study underscores the need for a feedback loop between public agencies and stakeholders to refine strategies in real time. These measures aim to improve coordination and effectiveness in mitigating future animal disease outbreaks.

In South Korea, mountainous regions constitute over 62% of the total land area. Recently, the incidence of landslides triggered by heavy summer rains attributed to climate change has increased. In particular, the occurrence of falling rocks is responsible for 40% of the collapses that occur in road cuttings. This study conducted an analysis of drone photography and an on-site survey in order to investigate the causes of damage to the Rock Shed and road resulting from landslides and the collapse of steep slopes in Bongyang-ri, Jeongseon-gun, Gangwon-do. The survey of the landslide-affected area revealed the formation of numerous fault breakers on the surveyed slope due to the crushing action induced by fault motion. We used 3D LiDAR survey data to create cross-sections at 10-meter intervals and then create a topline for each rockfall pile to estimate the overall scale of the event. This is the most accurate way to estimate the scale of activity. The analysis revealed that the volume of rockfall resulting from slope collapse amounted to 17,000 tons.

Background: This study attempted to prevent and strengthen the cognitive function of elderly people diagnosed with mild cognitive impairment in the pre-dementia stage through the cognitive rehabilitation program, ‘Hello! Aloha Yangsan’. Method: The subjects of this study were elderly people with mild cognitive impairment registered at a public health center in Y city, including a 25 experimental group and a 23 control group. The cognitive rehabilitation program was operated for a total of 24 sessions over 12 weeks, twice a week, with each session lasting 60 minutes. Results: The experimental group that participated in this intervention program showed a significant increase in cognitive function compared to the control group (t=-2.983, p=.005), and the subjective memory decline of the experimental group showed a significant decrease compared to the control group (t=42.66, p=.001). Conclusions: This intervention program was able to confirm significant effects on cognitive function, subjective memory decline, and depression, and can be used as a major basis for preventing the transition from mild cognitive impairment, which is a pre-stage of dementia to dementia in the future.

This study aims to develop a predictive model for student counseling support by identifying key individual factors encountered in university life, such as academic performance, financial conditions, psychological factors, and campus environment, as explanatory variables. Using logistic regression (logit model), the model was constructed to predict academic persistence and dropout, set as binary response variables, and validated for consistency through the support index. Additionally, the consistency of the dropout prediction model based on the logit model was cross-validated using a classification model with CART (Classification and Regression Tree) to determine which model or approach provided superior results. Modeling and comparing 2,000 simulated data points yielded similar results. All explanatory variables, except gender, were significant (p < .05), and, considering odds ratios, the number of leaves of absence (1.7818) and academic warnings (1.2921) had strong positive effects on dropout likelihood. Conversely, academic year, number of enrolled semesters, and GPA showed a negative effect on dropout probability. From a practical perspective for system implementation and operation, the logit model proved more efficient for constructing and applying the prediction model.

The purpose of this study is to provide foundational data for obesity management program using a chatbot by identifying the educational needs of high school girls. Data collection was carried out using focus group interviews with recruiting via social media. Interviews were conducted with three groups with a total of nine participants. All interview content was recorded and transcribed verbatim by the researcher, and the data were analyzed using qualitative content analysis. The study identified a total of 39 concepts, which were categorized into 16 subcategories and seven main categories. The seven main categories for a weight management program using a chatbot that participants desire were: : “Setting Weight Loss Goals,” “Emotional Regulation and Stress Management,” “Dietary Planning and Coping with Failures,” “Maintaining a Sense of Achievement After Exercise,” “Alleviating Concerns about Appearance,” “Privacy Protection and Confidentiality,” and “Effective Media.” Additionally, high school girls expected that using a chatbot would make it easier to address their questions and concerns related to weight management. Based on the results of this study, developing a chatbot-based obesity management program for high school girls and to verifying is needed.