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Three novel air terminal devices (ATDs) for localized ventilation were designed (ATD with perforated inner plate, ATD with honeycomb diffuser, and ATD with lobbed nozzle). The ability of the ATDs to provide clean air to the breathing zone of a person lying in a hospital bed was studied. Experiments were performed in a simulated full-scale hospital patient room. A thermal manikin was used to simulate a patient. The ATD was located above the head of manikin. Heated dummy simulated a doctor standing beside the bed. Tracer gas was used to simulate contaminated air exhaled by the doctor. The supply and the exhaust flow rates were controlled at 15.3 L/s and 14.8 L/s, respectively. The supply air temperature and room temperature were kept at 23 °C and 25.3 °C, respectively. Increase of the supply air speed resulted in a cleaner air supply to the breathing zone but also increased the risk of draught. The ATD with a lobbed jet nozzle was able to reduce contaminants by more than half in the breathing zone and to provide the lowest draught risk at the face. This ATD is a better solution to supply clean air in practice comparing to the other two ATDs.

An adaptive learning model for English vocabulary through a machine learning is proposed in this paper. The four main types of user information, including basic student information, quiz information, course video viewing information, and forum interaction information, are processed through feature engineering, and a better model on sparse data is proposed through comparison on different models, and the prediction accuracy of the model is improved through natural language processing techniques, to achieve feedback on user learning efficiency through user data and provide teachers and students with the corresponding teaching and learning suggestions for teachers and students. It is found that the quiz information has more influence than the course video viewing information, and the accuracy is improved by about 3% compared with TF-IDF after introducing word embedding. The use of mobile for English learners to learn to read in a fragmented learning context enables targeted training in weak areas of English reading, thus improving different aspects of learners' reading skills.

A novel range hood (NRH) consisting of a high-efficiency particulate air (HEPA) filter circulation component and exhaust component was designed to improve indoor air quality. The HEPA filter circulation component with an airflow rate of 72 l/s was used to remove the particulate matter generated by cooking activities and return filtered clean air to the room. The exhaust component was used to reject both particulate matter and other indoor air pollutants to the outdoors. Field measurements were carried out in an open kitchen of a two-floor residential house. The total occupied zone was about 160 m³ with a living area of 64 m2 (including an open kitchen) and a height of 2.5 m. Frying bacon that can generate a large number of particles of different sizes was used to simulate the daily cooking activities. Four operating conditions of the NRH were studied, i.e. 38 l/s exhaust airflow rate with the HEPA circulation on and off, and 78 l/s exhaust airflow rate with the HEPA circulation on and off. The concentration of PM0.1 count, PM2.5 mass, and PM10 mass were measured during measurements. The HEPA filter circulation part of the NRH can dramatically reduce the concentration of all sizes of particles generated by cooking activities. By combining the HEPA filter circulation component, the NRH can separately reduce the concentration of PM0.1, PM2.5, PM10 by up to 91.9%, 95.7%, 94.6% compared to that when only running the exhaust part.