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Noise in restaurants affects diners and service employees. Normally, people will not eat alone. They would rather enjoy good food and drink with business partners, friends, and family in restaurants and unavoidably they talk happily and loudly. Speeches from other restaurant patrons, service employees, mingling with background music and noise from ventilation systems, will interfere with communication between a talker and listeners. This paper presents a territory-wide noise survey in Hong Kong restaurants and presents a mathematical model that describes the background noise level in restaurants. The measured noise levels show that restaurant noise ranged from 66.7 to 82.6 dBA with a mean value of 73.9 dBA (SD = 3.81 dBA) while the mathematical model illustrates that the background noise level in restaurants mainly depends on the occupancy density. The model was validated by another tw o sets of noise measurement data recorded in other restaurants. The time record of noise measurement shows that the variation of noise levels decreases when the occupancy density increases. People have to raise their voice e ffort to improve their speech intelligibility in a very noisy environment. [ABSTRACT FROM AUTHOR]

Abstract: It is generally agreed that respiratory disease is closely related to ambient air quality and weather conditions. Besides, hygiene related factors such as the public health measures by the government and possible personal awareness in the community can also affect the spread of infectious respiratory diseases. However, there is no quantitative support for this conclusion, because of lack of quality data. The severe acute respiratory syndrome (or SARS) outbreak in 2003 triggered strict public health measures and personal awareness in the prevention of infectious respiratory diseases, providing us an opportunity to quantify the impact of hygiene related factors in the spread of the disease. In this paper, we model the number of the respiratory illnesses by a semiparametric model which models the environmental and weather impacts using a multiple index model and the impact of other public health measures and possible personal awareness using a growth curve with jump. Using data from Hong Kong, we found that public health measures contributed to about 39% of reduction in the number of respiratory illnesses during the SARS period. However, the impact of hygienically related factors eventually fades as time passes. The results provide indirect quantitative support to the usefulness of governmental campaigns to arouse the awareness of the public in staying away from transmission of respiratory diseases during the full outbreak of the disease. The results also show the fast fading of alertness of Hong Kong people towards the epidemic. Furthermore, our model also offers a way to model the impacts of environmental factors on respiratory diseases, when the data contains the effect of human intervention, by introducing the change point and growth curve to remove such an effect. [Copyright &y& Elsevier]

Abstract: In this paper, we derive a new class of flexible threshold asymmetric Generalized Autoregression Conditional Heteroskedasticity (GARCH) models. We use this tool for analysis and modeling of the properties that are apparent in many financial time series. In general, the transmission of volatility in the stock market is time-varying, nonlinear, and asymmetric with respect to both positive and negative results. Given this fact, we adopt the method of fuzzy logic systems to modify the threshold values for an asymmetric GARCH model. Our simulations use stock market data from the Taiwan weighted index (Taiwan), the Nikkei 225 index (Japan), and the Hang Seng index (Hong Kong) to illustrate the performance of our proposed method. From the simulation results, we have determined that the forecasting of volatility performance is significantly improved if the leverage effect of clustering is considered along with the use of expert knowledge enabled by the GARCH model. [Copyright &y& Elsevier]