Evaluation of ventilation performance in public spaces.

Smoking restrictions in the workplace and increased health consciousness at home have seen a sizable reduction in the number of spaces where smoking is permissible. The aim of this study was to investigate the effects of ventilation in public houses, one of the few remaining public spaces where smoking is still socially acceptable. Little is known about the situation with shared occupancies, where relatively large areas are intended to accommodate both smokers and non-smokers. This study clearly identifies potential problems with a simplistic design approach to ventilation and its effectiveness in the context of shared occupancy spaces. A computational fluid dynamics code has been used to model airflows with the aim of identifying inefficiencies in existing ventilation systems.

Natural Language Generation enhances human decision-making with uncertain information.

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different informa- tion presentations for uncertain data and, for the first time, measure their effects on human decision-making. We show that the use of Natural Language Genera- tion (NLG) improves decision-making un- der uncertainty, compared to state-of-the- art graphical-based representation meth- ods. In a task-based study with 442 adults, we found that presentations using NLG lead to 24% better decision-making on av- erage than the graphical presentations, and to 44% better decision-making when NLG is combined with graphics. We also show that women achieve significantly better re- sults when presented with NLG output (an 87% increase on average compared to graphical presentations).