Tourism experiences are inherently multisensory, engaging visitors’ senses of sight, sound, smell, taste, and touch. This study addresses the gap in literature by investigating the impact of visual and auditory landscapes on tourist emotions and behaviors within coastal tourism settings, using the Stimulus-Organism-Response (SOR) model. Data collected from tourists in Sanya, China, were analyzed using structural equation modeling. The results indicate that both visualscape and soundscape significantly influence tourist emotions (pleasure and arousal) and subsequent loyalty. Pleasure and arousal mediate the relationships between environmental stimuli and tourist loyalty, emphasizing their roles as emotional bridges between the environment and behaviors. These findings highlight the importance of integrating local cultural and community elements into tourism to enhance socio-economic benefits and ensure sustainable development. By fostering a deep connection between tourists and the local environment, these sensory experiences support the preservation of cultural heritage and promote sustainable tourism practices, aligning with the goals of economic development and public policy. The study contributes to the theoretical understanding of multisensory tourism by integrating the SOR model in coastal tourism and emphasizes the roles of visual and auditory stimuli. Practically, it provides insights for tourism managers to improve tourist experiences and loyalty through careful management of sensory elements. This has implications for infrastructure development, particularly in enhancing the quality of soft infrastructure such as cultural and social systems, which are crucial for sustainable tourism and community well-being. Future research could include additional sensory dimensions and diverse destinations for a comprehensive understanding of sensory influences on tourist behaviors and emotions. This research aligns with the broader goals of the policy and development by addressing critical aspects of infrastructure and socio-economic development within the tourism sector.

This study explores the transformative role of art design interventions in the sustainable development and infrastructure enhancement of intangible cultural heritage, with a particular focus on honored brands. The research develops a framework that positions aesthetic and interactive art design interventions as pivotal components in revitalizing these brands. Aesthetic interventions translate the brand’s core philosophy, spirit, and values into compelling visual symbols, harmonizing cultural heritage with modern image design to elevate brand reputation and consumer preference. Interactive interventions enhance user experience, particularly among younger demographics, by integrating technological and entertainment-based engagement, thereby strengthening consumer loyalty and brand influence. The study further investigates how these art design interventions serve as catalysts for broader social development, contributing to the modern relevance and societal impact of time-honored brands. Additionally, it examines the impact of these interventions on sustainable development, societal support, and policy alignment. By weaving together these elements, the research underscores the critical importance of aligning brand strategies with societal goals, fostering environments where brands actively contribute to social welfare and sustainable growth. The findings offer valuable theoretical insights and practical strategies for the sustainable development of time-honored brands, providing clear directions for future research and practice.

This study explores the impact of technology effectiveness, social development, and opportunities on higher education accessibility in Myanmar, focusing on private higher education institutions. Utilizing a sample of 199 respondents, with an average age of X (SD = Y), the research employs standardized questionnaires and descriptive statistics, correlation analysis, and multiple regression analysis to examine the relationships between these variables. The findings indicate that technology effectiveness significantly enhances higher education accessibility, with strong positive correlations (r = 0.752, p < 0.001) and substantial impacts on educational outcomes (β = 0.334, p = 0.001). Social development also plays a crucial role, demonstrating that supportive social norms and community engagement significantly improve accessibility (β = 0.405, p < 0.001). Opportunities provided by technological advancements further contribute to enhanced accessibility (β = 0.356, p < 0.001), although socio-political and economic challenges pose significant barriers. The study highlights the interconnectedness of these factors and their collective influence on educational accessibility. Practical implications include the need for strategic investments in technological infrastructure, promotion of supportive social environments, and innovative solutions to leverage opportunities. Future research directions suggest longitudinal studies, broader demographic scopes, and in-depth analyses of specific technological and infrastructural challenges. By addressing these areas, stakeholders can develop effective strategies to improve higher education accessibility, ultimately contributing to the socio-economic development of Myanmar.

The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.