Using data mining methods to remove uncertainties in sensor data streams. This project will develop key techniques for removing uncertainties in sensor data streams and thus improve the monitoring quality of sensor networks. The expected outcomes will benefit Australia by enabling improved, lower-cost monitoring of natural resources and management of stock raising.
Synthetic phenazines for enhanced biogas production from renewable and non-renewable resources. Methane (biogas) has a large role to play in meeting the energy needs of the human race globally whilst reducing greenhouse gas emissions. Microbial communities are responsible for biogas production from non-renewable (coal) and renewable (food waste) resources. This project seeks to: increase biogas yields by redirecting electron flow towards biogas producing microbes using electrochemically active p ....Synthetic phenazines for enhanced biogas production from renewable and non-renewable resources. Methane (biogas) has a large role to play in meeting the energy needs of the human race globally whilst reducing greenhouse gas emissions. Microbial communities are responsible for biogas production from non-renewable (coal) and renewable (food waste) resources. This project seeks to: increase biogas yields by redirecting electron flow towards biogas producing microbes using electrochemically active phenazines; understand the molecular mechanism by which phenazines increase biogas yields; and, assess the environmental consequence of phenazine application to coal seam gas production and anaerobic digestion of food waste. Phenazines are likely to emerge as a safe and cost-effective technology for improved biogas generation.Read moreRead less
A more intelligent knowledge-based system apprentice. Our previous techniques already had an impact on Australian industry, with five Australian companies marketing such technology, and for three of these it is a central technology. We expect an early uptake of the enhancements we propose by these companies, greatly increasing their international competitiveness against other rule technologies. Three of these companies are very recent, so we would expect other company uptake of the new enhance ....A more intelligent knowledge-based system apprentice. Our previous techniques already had an impact on Australian industry, with five Australian companies marketing such technology, and for three of these it is a central technology. We expect an early uptake of the enhancements we propose by these companies, greatly increasing their international competitiveness against other rule technologies. Three of these companies are very recent, so we would expect other company uptake of the new enhanced technology. In turn Australian companies using the technology will improve their competitiveness in an increasingly knowledge-based economy by being able to more rapidly and easily deploy knowledge-based systems. Our previous techniques have already had a significant impact in medical practice.Read moreRead less
Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact netw ....Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact networks to develop robust predictions of disease spread and population fate, and to reliably predict the outcomes of management interventions. These robust prediction methods will provide better insights for conservation of Australian wildlife.Read moreRead less