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.

To evaluate the efficiency of decision-making units, researchers continually develop models simulating the production process of organizations. This study formulates a network model integrating undesirable outputs to measure the efficiency of Vietnam’s banking industry. Employing methodologies from the data envelopment analysis (DEA) approach, the efficiency scores for these banks are subsequently computed and comparatively analyzed. The empirical results indicate that the incorporation of undesirable output variables in the efficiency evaluation model leads to significantly lower efficiency scores compared to the conventional DEA model. In practical terms, the study unveils a deterioration in the efficiency of banking operations in Vietnam during the post-Covid era, primarily attributed to deficiencies in credit risk management. These findings contribute to heightening awareness among bank managers regarding the pivotal importance of credit management activities.

Targeted Poverty Alleviation refers to the targeted funding work completed in the process of higher education development. However, at present, in the process of implementing the requirements of Targeted Poverty Alleviation in China's universities, some students' families are difficult to complete identification, and there are also some problems in the information management of the funders, which has seriously affected the funding for students with financial difficulties in their families during the period of higher education in China. With the rapid development and progress of Big data technology, through the establishment of a sound information technology system, we must help students actively change the funding model in the future and greatly improve the funding, which is of great significance to the development of university funding supervision and management.

Purpose: This study aims to clarify the meaning of sport analysis, explore the contributions derived from sporting event analysts, and highlights the importance of responsible sport gambling. It also investigates how sustainable practices can be integrated into sports analysis to enhance social well-being. Design/methodology/approach: Secondary text data from government documents, news articles, and website information were extracted by searching keywords such as sports lottery and sports analysis in traditional Chinese, and then analyzed to establish the research framework and scope. Subsequently, 18 interviews were conducted with stakeholders to gain deeper insights. Findings: The content analyses reveals that sport analysis tends to be sport data science. Sporting event analysts may contribute to improving the performance of players or a team, enhancing spectator sports, and increasing sports lottery revenues. In the leisure aspect, the professionalism of sporting event analysts not only increases epistemic and entertainment values in spectator sports but also boosts engagement with sport lotteries. To ensure these enhancements remain beneficial, it is vital to emphasize responsible sport gambling and sustainable practices that protect vulnerable groups and promote long-term health benefits for those involved in sports. The integration of sustainable practices in sport analysis and the expertise of sporting event analysts can significantly advance economic and social development by generating funds through sport lottery industry for athlete programs, sports infrastructure, and educational initiatives, aligning with multiple Sustainable Development Goals. Additionally, the professionalism of these analysts may enhance public understanding and engagement of sports, promoting increased participation in sports, reducing healthcare costs, and contributing to the development of a healthier and more resilient society. Originality: Emphasizing responsible sports gambling is essential to the sustainability of sports lotteries and the role of sporting event analysts.

Although dykes are a predominant and widely distributed phenomenon in S-Algeria, N-Mali and N-Niger, a systematic, standardized inventory of dykes covering these areas has not been published so far. Remote sensing and geo information system (GIS) tools offer an opportunity for such an inventory. This inventory is not only of interest for the mining industry as many dykes are related to mineral occurrence of economic value, but also for hydrogeologic investigations (dykes can form barriers for groundwater flow). Surface-near dykes, major fault zones, volcanic and structural features were digitized based on Landsat 8 and 9, Sentinel 2, Sentinel 1 and ALOS PALSAR data. High resolution images of World Imagery files/ESRI and Bing Maps Aerial/Microsoft were included into the evaluations. More than 14,000 dykes were digitized and analyzed. The evaluations of satellite images allow a geomorphologic differentiation of types of dykes and the description of their characteristics such as dyke swarms or ring dykes. Dykes are tracing zones of weakness like faults and zones with higher geomechanically strain. Dyke density calculations were carried out in ArcGIS to support the detection of dyke concentrations as stress indicator. Thus, when occurring concentrated, they might indicate stressed areas where further magmatic and earthquake activity might potentially happen in future.