Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Enhancing the trust of location acquisition systems for critical applications and location-based security services

This paper identifies a number of critical infrastructure applications that are reliant on location services from cooperative location technologies such as GPS and GSM. We show that these location technologies can be represented in a general location model, such that the model components can be used for vulnerability analysis. We perform a vulnerability analysis on these components of GSM and GPS location systems as well as a number of augmentations to these systems.

Improving the Flexibility of Active Grids through Web Services

Active Grids are a form of grid infrastructure where the grid network is active and programmable. These grids directly support applications with value added services such as data migration, compression, adaptation and monitoring. Services such as these are particularly important for eResearch applications which by their very nature are performance critical and data intensive. We propose an architecture for improving the flexibility of Active Grids through web services. These enable Active Grid services to be easily and flexibly configured, monitored and deployed from practically any platform or application. The architecture is called WeSPNI ('Web Services based on Programmable Networks Infrastructure'). We present the architecture together with some early experimental results on using web services to monitor data movement in an active grid.