• Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction

      Chen, Long; Tang, Wen; Zhang, Jian Jun; John, Nigel W.; Bournemouth University; University of Chester; University of Bradford (Wiley Online Library, 2019-11-14)
      Mixed Reality (MR) is a powerful interactive technology for new types of user experience. We present a semantic-based interactive MR framework that is beyond current geometry-based approaches, offering a step change in generating high-level context-aware interactions. Our key insight is that by building semantic understanding in MR, we can develop a system that not only greatly enhances user experience through object-specific behaviors, but also it paves the way for solving complex interaction design challenges. In this paper, our proposed framework generates semantic properties of the real-world environment through a dense scene reconstruction and deep image understanding scheme. We demonstrate our approach by developing a material-aware prototype system for context-aware physical interactions between the real and virtual objects. Quantitative and qualitative evaluation results show that the framework delivers accurate and consistent semantic information in an interactive MR environment, providing effective real-time semantic level interactions.
    • A Review of Piezoelectric and Magnetostrictive Biosensor Materials for Detection of COVID‐19 and Other Viruses

      Narita, Fumio; Wang, Zhenjin; Kurita, Hiroki; Li, Zhen; Shi, Yu; Jia, Yu; Soutis, Constantinos; Tohoku University; Nanjing University of Aeronautics and Astronautics; University of Chester; Aston University; University of Manchester
      The spread of the severe acute respiratory syndrome coronavirus has changed the lives of people around the world with a huge impact on economies and societies. The development of wearable sensors that can continuously monitor the environment for viruses may become an important research area. Here, the state of the art of research on biosensor materials for virus detection is reviewed. A general description of the principles for virus detection is included, along with a critique of the experimental work dedicated to various virus sensors, and a summary of their detection limitations. The piezoelectric sensors used for the detection of human papilloma, vaccinia, dengue, Ebola, influenza A, human immunodeficiency, and hepatitis B viruses are examined in the first section; then the second part deals with magnetostrictive sensors for the detection of bacterial spores, proteins, and classical swine fever. In addition, progress related to early detection of COVID‐19 (coronavirus disease 2019) is discussed in the final section, where remaining challenges in the field are also identified. It is believed that this review will guide material researchers in their future work of developing smart biosensors, which can further improve detection sensitivity in monitoring currently known and future virus threats.