Vol. 1 No. 2 (2023)
Editorial Introduction to the October 2023 Issue of Cambridge Explorations in Arts and Sciences (CEAS)
On behalf of the Editorial Team, I would like to welcome you to the October issue of Cambridge Explorations in Arts and Sciences (CEAS). As Editor-in-Chief, I am delighted to announce that this issue is wide-ranging with topics from technical fields such as machine learning and artificial intelligence (AI) as applied to viral spread, deep neural networks, financial technology, image reconstruction, driver assistance and parking assistance, robotic arm improvement, disease modelling, and plant conservation. On the social sciences side, topics include digital museums, and the nature-nurture debate. As with our June 2023 issue, 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 the first of our eleven papers, Xiao Yuxuan et al. revisit the nature-nurture debate and generate novel results by conducting inter-cultural fieldwork based on a combined online-offline questionnaire. Then, Wang Mingjie et al. create a dynamic model to analyse the behaviour of an epidemic by linking infecting to infected people with the goal of limiting viral spread, while Xia Mingwei et al. conduct a thorough investigation of users’ experiences of the digital museum as compared with the physical experience. They identify many gaps where the digital experience can be improved. Taking us into nature conservation, Deng Chuyu et al. examine traditional ecosystem mapping methods and compare them to results generated by the CAPTAIN artificial intelligence-based system. They make a strong case that the AI approach supersedes the traditional and represents a leap forward. Next comes medical technology, advancing rapidly. Robotic arms are an important part of neurorehabilitation and Chen Wenyi et al. propose an EEG-based control method to enhance their function. With many applications, the paper by Xu Xiaotang et al. is specifically focussed on deep neural networks and they evaluate single and ensemble attack methods. Xu Yingche et al., on the other hand, tackle the issue of image reconstruction and how it can be enhanced by a combined use of VAEs and Planar Flows drawing on machine learning. Driverless cars are becoming all the more common. Shi Yutian et al. deploy artificial intelligence for assisted driving and put forward certain solutions to specific problems encountered today in the area of safety that are achievable by harmonising existing advanced driver assistance and driver state monitoring systems. Continuing in the theme of driving, Li Wenxuan et al. address the problem faced by all drivers - where to park. They modify a ResNet model with transfer learning to produce a solution that helps drivers in the smart city and potentially eases congestion. Turning to the world of finance, Yuan Yiwei et al. examine the use of the sandbox as a tool for evaluating potential financial regulation. As a result of a comparison of current use in the UK, Singapore, and China they make concrete proposals as to how the Chinese process could be improved. Going further in the area of financial technology, Cheung Arts et al. review the use of cryptocurrencies in Hong Kong and China and make policy recommendations for their future use in China.
Mark Perkins
Editor-in-Chief
