Conference Agenda

The cutting-edge technology called Digital Twinning is being developed for use in several applications, including, but not limited to, the Departments of Transportation, Defense Industry, Supply Chain, and Cyber Security. This study investigates the theoretical basis for DT, the state of the art, and ideas for academic research in this area. It has been the fastest-growing technology in the simulation since 2017, and nations are trying to catch up. Through a demonstration of the technology, interviews with key stakeholders, and Transportation Research Board survey results, this study examines the multiple opportunities for research and education in DT. Enabling technologies are also presented.

Economic inequality significantly impacts individuals seeking affordable professional advice related to health, legal matters, and financial decisions. Artificial Intelligence (AI) applications can provide individuals with inexpensive, timely, and anonymous advice, addressing their concerns without jeopardizing financial stability. AI applications can foster critical thinking and informed decision making by offering broader insights and viewpoints. Despite AI advantages, AI should be used in conjunction with human experts. This study examines ways AI can leverage human experts while providing an affordable option for the economically disadvantaged. We will conduct a study collecting data from human experts in law, health, and finance. Based on the results of the study, we propose a model and best practices for organizations designing, developing, and deploying AI applications that provide legal, health, or financial advice.

While large language models (LLMs) like ChatGPT have seen widespread adoption in higher education, there remains a significant gap in the research literature regarding the following questions: How does the utilization of LLMs impact student learning experiences and instructional design practices within higher education, particularly in the context of business college education? To address these inquiries, a mixed-methods approach will be employed. The research plan entails conducting a comprehensive literature review to systematically outline ChatGPT's capabilities. Qualitative data will be collected through semi-structured interviews with both educators and students, aiming to gain valuable insights into the experiential aspects of incorporating ChatGPT into instructional methods and enhancing student learning. Subsequently, a framework will be developed for integrating ChatGPT into instructional design within business college education, with the primary goal of improving student learning experiences. Quantitative data will also be collected through surveys to validate the effectiveness of the proposed framework.

Transportation and logistics in mountainous regions are challenging due to harsh weather conditions and complex terrain. It's crucial to have specialized expertise and advanced technologies to tackle such challenges. However, the field has unexplored domains, and innovative solutions are not holistically charted, necessitating a nuanced understanding of technological landscapes and growth trajectories. This study aims to undertake a patent analysis on mountain transport vectors to unveil emerging trends, map technological structures, and contribute to enhancing transportation systems. We conducted topic modeling to identify and group relevant technological fields from patent documents. Our analysis identified twelve specialized areas in mountain transport vectors. Among emerging areas, seat and suspension control systems, intelligent vehicle control systems, electric vehicles, bicycle frame design, and safety devices have potential significance in the future of mountain transportation. These findings have practical implications for industry stakeholders and contribute to academic discourse on mountain logistics.

This study was funded by the European Union - NextGenerationEU, in the framework of the iNEST - Interconnected Nord-Est Innovation Ecosystem ( iNEST ECS00000043 – CUP I43C22000250006). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them.