Improved design and operational efficiency of small wind turbines in unsteady flows. The purpose of this research is to improve the design and performance of small wind turbines for energy generation. The expected outcomes are novel control strategies and mechanical designs that account for unsteady aerodynamics and its effects on structural loads and power quality. Recommendations to improve current design standards will be made.
Design of Functionalized Mesoporous Fullerenes for Clean Energy. This project aims to design multifunctional, noble metal-free, and highly ordered mesoporous fullerene with a high conductivity and different porous structures, functionalised with nitrogen and/or metal and metal oxide nanoparticles in both powder and film forms. The most promising, stable, and highly efficient noble metal-free electrode catalyst system will be designed with the functionalised mesoporous fullerenes for polymer elec ....Design of Functionalized Mesoporous Fullerenes for Clean Energy. This project aims to design multifunctional, noble metal-free, and highly ordered mesoporous fullerene with a high conductivity and different porous structures, functionalised with nitrogen and/or metal and metal oxide nanoparticles in both powder and film forms. The most promising, stable, and highly efficient noble metal-free electrode catalyst system will be designed with the functionalised mesoporous fullerenes for polymer electrolyte membrane and direct methanol fuel cells. This novel highly efficient and low cost electrode system for fuel cells aims to help address clean energy generation and environmental problems and create new opportunities for Australian industries.Read moreRead less
Market segmentation methodology: attacking the 'Too Hard' basket. Businesses embrace market segmentation to identify and target clients. However, poor segmentation analysis leads to poor segment choice. This project will develop tools to improve segmentation analysis and will test the resulting tools in tourism, foster care and climate change mitigating behaviours, and produce usable, transferable recommendations.
Carbon dioxide in water nanoemulsions for carbon sequestration. The project will address a key objection to geological carbon dioxide (CO2) sequestration by removing the risk of long-term leakage to drinking water aquifers or to atmosphere. By injecting a nano-emulsion of CO2-in-water, the project seeks to show complete reaction to permanently stable solid carbonate occurs within weeks, eliminating the need for secure caprock or extended seal integrity monitoring. New knowledge will be generated ....Carbon dioxide in water nanoemulsions for carbon sequestration. The project will address a key objection to geological carbon dioxide (CO2) sequestration by removing the risk of long-term leakage to drinking water aquifers or to atmosphere. By injecting a nano-emulsion of CO2-in-water, the project seeks to show complete reaction to permanently stable solid carbonate occurs within weeks, eliminating the need for secure caprock or extended seal integrity monitoring. New knowledge will be generated using innovative approaches to create and stabilise CO2-in-water nano-emulsions and demonstrate the fast conversion of CO2 into stable minerals. The benefits are significant in opening potential sequestration targets to include areas without secure caps, reduced cost and elimination of long-term leakage riskRead moreRead less
Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive ....Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive and specific detection of early cancers, the potential reductions in morbidity and mortality from breast cancer will be of immense value. Successful implementation of the proposed project will further enhance Australia's position as a world leader in biomedical research and application of computational technologies to health problems.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Taming the uncertainty in trajectory data. This project aims to develop effective and efficient methods to manage large scale uncertain trajectory data. It provides individuals, business, government and social groups the ability to explore significant uncertain trajectories and their patterns, for important usages in location based services, logistic, transportation and tourism.
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less
Membrane Systems for CO2 Capture and Conversion Using Multi-Enzyme Cascades. Carbon capture and storage (CCS) is one of the defining technological challenges in today's industry and society. Primary sources of carbon dioxide (CO2) are due to energy generation using fossil fuels as well as key manufacturing activities such cement production and steel making. This project aims to focus on novel approaches to enzyme mediated membrane contactor systems to create robust, high efficiency CO2 capture f ....Membrane Systems for CO2 Capture and Conversion Using Multi-Enzyme Cascades. Carbon capture and storage (CCS) is one of the defining technological challenges in today's industry and society. Primary sources of carbon dioxide (CO2) are due to energy generation using fossil fuels as well as key manufacturing activities such cement production and steel making. This project aims to focus on novel approaches to enzyme mediated membrane contactor systems to create robust, high efficiency CO2 capture from post-combustion and other gas emissions and conversion into useful chemical feedstock. Enzyme immobilisation and stabilisation are expected to be enhanced using functionalised nanoparticles and nanostructured membranes.Read moreRead less