The freight transport chain brings together several types of players, particularly upstream and downstream players, where it is connected to both nodal and linear logistics infrastructures. The territorial anchoring of the latter depends on a good level of collaboration between the various players. In addition to the flow of goods from various localities in the area, the Autonomous Port of Lomé generates major flows to and through the port city of Lomé, which raises questions about the sustainability of these various flows, which share the road with passenger transport flows. The aim of this study is to analyse the challenges associated with the sustainability of goods flows. The methodology is based on direct observations of incoming and outgoing flows in the Greater Lomé Autonomous District (DAGL) and semi-directive interviews with the main players in urban transport and logistics. The results show that the three main challenges to the sustainability of goods transport are congestion (28%), road deterioration (22%) and lack of parking space (18%).

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.

The growth of buildings in big cities necessitates Design Review (DR) to ensure good urban planning. Design Review involves the city community in various forms; however, community participation remains very limited or even non-existent. There are indications that the community has not been involved in the Design Review process. Currently, DR tends to involve only experts and local government, without including the community. Therefore, this research aimed to analyze the extent of opportunities for community participation by exploring DR analysis in developed countries and related policies. In-depth interviews were also carried out with experts and Jakarta was selected as a case study since the city possessed the most intensive development. The results showed that the implementation of DR did not consider community participation. A constructivist paradigm was also applied with qualitative interpretive method by interpreting DR data and community participation. The strategy selected was a case study and library research adopted by examining theories from related literature. Additionally, the data was collected by reconstructing different sources such as books, journals, existing research, and secondary data from related agencies. Content and descriptive analysis methods were also used, where literature obtained from various references was analyzed to support research propositions and ideas.

The research aims to investigate the prospective implications of Artificial Intelligence (AI) on traditional media, and to elucidate the conceptualization of AI within the discourse of media professionals, governmental and private media stakeholders in Jordan, alongside media scholars and IT experts. Employing the focus group method, a specialized interview tool distinguished by its purpose, design, and procedures, two distinct cohorts were engaged: media practitioners and officials on one hand, and academics and experts on the other. The investigation revealed the absence of a universally agreed upon terminology concerning AI, attributable to its nascent nature and rapid evolution. Notably, AI, leveraging its diverse and highly proficient tools, demonstrates significant potential for transformative impacts across various facets of the media landscape. These encompass the facilitation of exceptional content production, the empowerment of journalists to express their creative capacities, and substantial reductions in time, labor, and procedural overheads in media product development. Concurrently, the integration of AI within media environments is anticipated to pose formidable challenges to existing institutional frameworks. Additionally, the imperative of curriculum development in academic institutions, both public and private, is underscored to acquaint students with AI methodologies.

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.

In Central and Eastern European countries, the labour shortage is becoming increasingly pronounced, posing a challenge for the economy. Labour shortages limit the potential national income as many positions remain unfilled, which could lead to a slowdown in economic growth. To address this issue, various solutions need to be explored. This research aims to analyze solutions for alleviating labour shortages, with particular emphasis on measures that encourage workforce participation. One strategy is introducing training and retraining programs that help workers develop skills and adapt to labour market demands. Another option is to promote part-time employment, which may be especially attractive to groups unable or unwilling to work full-time. Enhancing population mobility could also be crucial in addressing labour shortages, particularly in bridging regional disparities. Integrating certain inactive groups, such as retirees, homemakers, students, people with disabilities, and those with low education levels experiencing generational poverty, into the labour market could also yield significant benefits. The study employs quantitative analysis methods and includes a survey that examines citizens’ perspectives on the effectiveness of measures aimed at increasing labour market participation and their economic impact on the Slovak economy. The survey data were collected in 2023 in the region of Rožňava and its surrounding areas.