Vol. 2 No. 1 (2024)

Editorial Introduction to the January 2024 Issue of Cambridge Explorations in Arts and Sciences (CEAS) 

On behalf of the Editorial Team, I would like to welcome you to the January issue of Cambridge Explorations in Arts and Sciences (CEAS), our first of 2024. As Editor-in-Chief, I am pleased to see that this issue has a large spread of topics.  These include the impact of AI on the automotive sector, AI-enhanced walking aids for the elderly, and developments in remote sensing of small images. AI in economic decision-making is also tackled, as is AI and copyright. Materials science is represented through a nanoscale study of the properties of copper, and Bayesian models are examined with potential applications to neural networks. On the social sciences side, topics include a different perspective on digital museums, the nature of student discourse in the dormitory setting, and the use of AI in children’s painting. As with our previous issues, the papers have been written by university students on a Cambridge educational programme (please contact the Editor-in-Chief for details). 

Our Eleven Papers 

In their study of the automaker Haier, Wu Jingyi et al. found that AI applications have a powerful influence on R&D, productivity, defect rate, and carbon footprint, leading to an overall improvement in efficiency. Also in the automotive sector, Dai Le et al. examined the impact of artificial intelligence on the development of the carmaker BYD Co. AI appeared to improve all indicators, although the authors pointed to the need for a longer study than the 7 years of data available to them could afford. Then, Jiang Yulin et al. evaluated several walking aids for the elderly and suggested not only AI-enhanced improvements but also commercial prototypes. 

Kong Ziyang et al. tackled the difficult issue of remote sensing of small objects. They reviewed existing technologies and proposed improvements including a new visual interface. Zhu Yukai et al. address the interesting question of whether AI processing of data affects international economic policymaking. They also discuss the risks of AI use in formulating international economic policies from an ethical perspective, a hitherto neglected area. With the use of AI, Ling Hongyi et al. trained a convolutional neural network on copyright data to identify infringement. The model created gave an accuracy of 80%. Tang Minyu et al. made a detailed investigation of the properties of copper at the nanoscale level. The study contributes significantly to the understanding of copper’s mechanical properties and the application of computational simulation in material. In a highly technical paper, Chen Yankun et al. looked at the Auto-Encoding Variational Bayes (AEVB) estimator. Using the standard stochastic gradient method, they found that the estimator can be directly discretized and optimized, improving the existing dynamic Bayesian network and achieving substantial improvements in accuracy and efficiency relevant to time-series modeling and classification. 

On the humanistic side, Zhang Tianshu et al. present the results of a market analysis of young visitors to museums and show how a digital approach to the visitor experience will not only be beneficial but also possibly lead to increased employment. Next, from a linguistic and sociological point of view, Haoyang Guan et al. conducted a questionnaire of Chinese students in dormitories to investigate the discourse of conflict expressed by gender. They found clear differences as to the perception of conflict and its resolution mechanisms. Finally, Ye Lyuzhaozhao et al. conducted research on the use of AI as an assistant for children when making their paintings. The research was based on one in-depth case study combined with a questionnaire sent to adults. It was found that the child enjoyed using an AI tool and the results were evaluated positively overall by adults leaving scope for future use. 

I hope the reader will enjoy the diversity of research in our January issue! 

Mark Perkins 

Editor-in-Chief