South Korea’s over 3300 islands play vital roles in the nation’s geography, economy, culture, and national security. Despite their importance, these islands face significant challenges, including population decline, aging demographics, and a severe lack of healthcare, childcare, and education facilities. With only 20% of inhabited islands connected to the mainland by bridges, coastal ferries are the primary transportation mode. However, the infrequent ferry services and numerous intermediate stops cause considerable inconvenience. This study conducts an analysis of the coastal ferry route connectivity within the Mokpo Area, focusing on proposing improvements to enhance access to community infrastructure for local island residents. This study analyzes the Mokpo Area’s coastal ferry network, identifying Dochodo as a central hub island to improve connectivity for sustainable island development. By reorganizing routes around Dochodo with larger ferries for main routes and smaller ferries for local trips, the study aims to enhance service access and boost tourism for island communities.

This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.

Combining physical, social, and economic elements, urban planning plays a critical role in creating sustainable, resilient, and livable urban environments. It encompasses the regulation of land use, infrastructure, transportation systems, and environmental resources, with a focus on sustainable urban design and green infrastructure. While progress has been made, there are still areas that have not been fully explored, including the integration of renewable energy sources and the development of urban environments that are resilient to environmental stresses. This study aims to analyze the direction and scope of urban planning research and to identify research gaps in this area. The method used is bibliometrics by analyzing data obtained from the Scopus database in January 2024. The results of this study showed that Yufeng Zhang, a professor at Wuhan University, China, was the most productive author in producing publications, namely 22 documents. In addition, the article produced by Qianqian Zhou is also influential in this research topic because it gets a number of citations, as high as 204 citations. Additionally, the results indicate the current focus of research on sustainability, adaptation to climate change, and technology in urban planning. These findings can guide future research, direct policy, and ensure an interdisciplinary approach to modern urban and regional challenges.

The idea of emotions that is concealed in human language gives rise to metaphor. It is challenging to compute and develop a framework for emotions in people because of its detachment and diversity. Nonetheless, machine translation heavily relies on the modeling and computation of emotions. When emotion metaphors are calculated into machine translation, the language is significantly more colorful and satisfies translating criteria such as truthfulness, creativity and beauty. Emotional metaphor computation often uses artificial intelligence (AI) and the detection of patterns and it needs massive, superior samples in the emotion metaphor collection. To facilitate data-driven emotion metaphor processing through machine translation, the study constructs a bi-lingual database in both Chinese and English that contains extensive emotion metaphors. The fundamental steps involved in generating the emotion metaphor collection are demonstrated, comprising the basis of theory, design concepts, acquiring data, annotating information and index management. This study examines how well the emotion metaphor corpus functions in machine translation by proposing and testing a novel earthworm swarm-tunsed recurrent network (ES-RN) architecture in a Python tool. Additionally, the comparison study is carried out using machine translation datasets that already exist. The findings of this study demonstrated that emotion metaphors might be expressed in machine translation using the emotion metaphor database developed in this research.

Background: Various studies have demonstrated the usefulness of Google search data for public health-monitoring systems. The aim of this study is to be estimated interest of public in infectious diseases in infectious diseases in South Korea, the five other countries. Methods: We conducted cross-country comparisons for queries related to the H1N1 virus and Middle East respiratory syndrome coronavirus (MERS-CoV). We analyzed queries related to the novel coronavirus disease (COVID-19) from 20 January to 13 April 2020, and performed time-descriptive and correlation analyses on trend patterns. Results: Trends in H1N1, MERS-CoV, and COVID-19 queries in South Korea matched those in the five other countries and worldwide. The relative search volume (RSV) for the MERS-CoV virus increased as the cumulative number of confirmed cases in South Korea increased and decreased significantly as the number of confirmed cases decreased. The volume of COVID-19 queries dramatically increased as South Korea’s confirmed COVID-19 cases grew significantly at the community level. However, RSV remained stable over time. Conclusions: Google Trends provides real-time data based on search patterns related to infectious diseases, allowing for continuous monitoring of public reactions, disease spread, and changes in perceptions or concerns. We can use this information to adjust their strategies of the prevention of epidemics or provide timely updates to the public.

Molan, an intangible cultural heritage of the Zhuang nationality in China, faces a crisis due to traditional communication and inheritance models. In the digital era, leveraging advanced digital technology is crucial for revitalizing this ancient heritage. From a communication theory perspective, this paper uses field investigation and applies the classic 5W communication model by Lasswell to deeply analyze the crisis facing Molan culture. Integrating the media evolution theory of Levinson, it explores the benefits and methodologies of digital dissemination for ancient intangible cultural heritage and proposes a digital communication model. The paper emphasizes adopting the PGC (Professional Generated Content) + UGC (User Generated Content) production model and strictly adhering to the “Content is King” principle. It advocates for models such as “Social Media + Molan,” “Short Video + Molan,” and “Algorithm + Molan” to enhance communication effectiveness. These viewpoints aim to revitalize and preserve Molan culture in the digital age.