Dynamic model of respiratory infectious disease transmission in urban public transportation systems.

During the epidemics of respiratory infectious diseases, the use of public transportation increases the risk of disease transmission. Therefore, we established a dynamic model to provide an in-depth understanding of the mechanism of epidemic spread via this route. We designed a computer program to model a rail transit system including four transit lines in a small town in which assumed 70% of the residents commute via these trams in weekdays and the remaining residents take the tram at random.

A dynamic model for elevator operation-induced spread of a respiratory infectious disease in an apartment building.

Residents have to use elevators to leave and enter their high-rise apartments frequently. An elevator car can easily spread respiratory infectious diseases, as it has a confined and small space. Therefore, studying how elevator operations promote epidemic transmission is of importance to public health.

Fast self-learning modulation recognition method for smart underwater optical communication systems.

Automatic modulation recognition (AMR) is an integral part of an intelligent transceiver for future underwater optical wireless communications (UOWC). In this paper, an orthogonal frequency division multiplexing (OFDM) based progressive growth meta-learning (PGML) AMR scheme is proposed and analyzed over UOWC turbulence channels. The novel PGML few-shot AMR framework, mainly suffering from the severe underwater environments, can achieve fast self-learning for new tasks with less training time and data.