Mediating role of artificial intelligence in the relationship between higher education quality and scientific research ethics among faculty members: A Study in carrying out the study, specific research objectives were derived, and based on the derived objectives, null hypotheses were formulated and tested for the study. This study, thus, employed survey research design. This study’s population comprised postgraduate students from Middle Eastern University, Jordan, with 1200 students. Using the population, a sample size of 291 respondents was selected based on Krecie and Morgan The students in the sample completed Google Forms questionnaires. The data were statistically processed, and the analysis’s most significant level was 0.25. The research questions were analyzed using descriptive statistics, and the null hypothesis was tested using Pearson Product Moment Correlational Analysis (PPMC). Also, the study showed a significant relationship between artificial intelligence and the quality of higher education and the relationship of significance between artificial intelligence and ethics in scientific research. The researcher suggested a need for ongoing education, cross-discipline cooperation, and the development of solid ethical frameworks for the integration ethics of AI academia.

Tourist visits to a destination or attraction as a result of the destination being featured on television, video, or the cinema screen were the ones, that stimulated the creation and development of film tourism, which quickly established itself in global conditions. The main objective of the paper was focused on the identification and the perception of the conditions of film tourism development in Slovak republic. So far, a lot of film production has been realized in the country, but this potential has not yet been properly used for the creation of tourism products. Implementation of the study from a methodological point of view took place using several research methods. The pilot scientific abstraction of the issue was followed by the analysis of film conditions in the territory of Slovak Republic and their categorization. The given starting points were followed by the implementation of questionnaire research, the results of which were verified using several research methods such as Doornik-Hansen test, Kruskal-Wallis test. The results of the questionnaire research show a significant positive perception of the potential of filmmaking as a significant factor in the creation of new tourism products. At the same time, they identify key destinations that could potentially become objects of product realization. Due to the fact that this issue has not received adequate attention in domestic conditions, the study brings a new, more comprehensive view of the topic and emphasizes the power of the potential for further development.

Brain tumors are a primary factor causing cancer-related deaths globally, and their classification remains a significant research challenge due to the variability in tumor intensity, size, and shape, as well as the similar appearances of different tumor types. Accurate differentiation is further complicated by these factors, making diagnosis difficult even with advanced imaging techniques such as magnetic resonance imaging (MRI). Recent techniques in artificial intelligence (AI), in particular deep learning (DL), have improved the speed and accuracy of medical image analysis, but they still face challenges like overfitting and the need for large annotated datasets. This study addresses these challenges by presenting two approaches for brain tumor classification using MRI images. The first approach involves fine-tuning transfer learning cutting-edge models, including SEResNet, ConvNeXtBase, and ResNet101V2, with global average pooling 2D and dropout layers to minimize overfitting and reduce the need for extensive preprocessing. The second approach leverages the Vision Transformer (ViT), optimized with the AdamW optimizer and extensive data augmentation. Experiments on the BT-Large-4C dataset demonstrate that SEResNet achieves the highest accuracy of 97.96%, surpassing ViT’s 95.4%. These results suggest that fine-tuning and transfer learning models are more effective at addressing the challenges of overfitting and dataset limitations, ultimately outperforming the Vision Transformer and existing state-of-the-art techniques in brain tumor classification.

The global Testing, Inspection, and Certification (TIC) service market is experiencing significant growth, driven by rising demand for high-quality and safety-related TIC services across various industries. This research aims to redesign a position map and strategy for Indonesian TIC State-Owned Enterprises (SOEs) in the Red Ocean competition. This systematic literature review analyzed 17 journals. The results show that the Indonesian TIC SOEs are intensively competing in the Red Ocean competition. In designing the position map in the Red Ocean competition, the SOEs must use technology in their operational activities to implement good corporate governance, collaborative strategies, resource management, and leadership styles aligned with the organizational culture.

Economic growth is a pressing issue facing the global community transitioning to sustainable development. Sustainable development is impossible without rapid economic growth limited by imperfect technologies and social structure. Most often, the limit of economic growth is related not so much to the amount of natural resources as to the possibilities of the environment. The atmosphere, water reservoirs, and the earth are already at the limit of their capabilities. This forces us to look for ways to develop production in combination with the economic and environmental spheres. Advanced companies are the first environmentally oriented enterprises, because reducing the amount of primary raw and other materials and energy, switching to secondary raw materials, and processing them reduces the cost of production, and, most often, brings additional profit. This study evaluates socioeconomic approaches to the development of the environmental management system. The creation of an environmentally friendly enterprise’s field of activity is not only a solution to many economic and environmental issues but also one of the ways to transition to a normally functioning market system, given the financial capabilities of enterprises and the understanding of the necessity of state sustainable development by the company management and the population.

Indonesia, as a maritime country, has many coastal areas with fishing villages that have significant potential, especially in sociological, economic, and environmental aspects, to be developed as models for sustainable development. Indonesia, with its long-standing fishing traditions, showcases the abundant potential and traditional that could help address global challenges such as climate change, rapid urbanization, and environmental and economic issues. This study aims to develop a conceptual model for sustainable cities and communities based on local potential and Wisdom towards the establishment of a Blue Village in the fishing village of Mundu Pesisir, Cirebon, Indonesia. The urgency of this study lies in the importance of developing sustainable strategies to address these challenges in coastal towns. This study involves an interdisciplinary team, including experts in sociology, social welfare, architecture, law, economics, and information technology. Through the identification of local natural and sociocultural resources, as well as the formulation of sustainable development strategies, this study develops a conceptual Blue Village model that can be applied to other coastal villages. The method employed in this study is qualitative descriptive, involving the steps of conducting a literature review, analyzing local potential, organizing focus group discussions, conducting interviews, and finalizing the conceptual model. The study employed, a purposive sampling technique, involving 110 participants. The results of the study include the modeling of a sustainable city and community development based on local potential and Wisdom aimed at creating Blue Villages in Indonesia, and It is expected to make a significant contribution to the creation of competitive and sustainable coastal areas capable of addressing the challenges of climate change and socioeconomic dynamics in the future.