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
Discovery Early Career Researcher Award - Grant ID: DE130100457
Funder
Australian Research Council
Funding Amount
$360,945.00
Summary
Dynamic fracturing in shale rock through coupled continuum-discontinuum modelling. The research includes modelling the grain level fracturing of shale rock under dynamic loads. The outputs will have a direct impact on the development and optimisation of rock drilling and rock cutting technologies and will improve the operational efficiencies in which rock excavations are conducted.
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
Preventing extreme granular wear of geotechnical machinery. This project will investigate the mechanisms controlling the mechanical wear that is incurred while handling geomaterials such as sand, ore, coal and fragmented rock. The overarching aim is to help forecast and mitigate extreme wear conditions by analysing the microscopic forces that granular materials produce when in contact with moving metallic surfaces. The intended outcomes include a thorough understanding of these interfacial inter ....Preventing extreme granular wear of geotechnical machinery. This project will investigate the mechanisms controlling the mechanical wear that is incurred while handling geomaterials such as sand, ore, coal and fragmented rock. The overarching aim is to help forecast and mitigate extreme wear conditions by analysing the microscopic forces that granular materials produce when in contact with moving metallic surfaces. The intended outcomes include a thorough understanding of these interfacial interactions and an experimentally validated theory predicting wear rates for a range of materials and handling processes. The expected benefit of this project is to enhance the productivity and reliability of the mining and construction sectors by reducing wear-related machinery failures.Read moreRead less
Robust learning of dynamic systems. Robots and other autonomous machines use models of the real world to predict the result of their actions and make decisions, but existing methods used for machine-learning are unreliable in many cases and can be easily fooled. This project aims to make machine-learning of dynamic system models reliable, accurate, and secure. The outcomes of this project will be new models and algorithms that ensure safety and increase accuracy of models learned from data. This ....Robust learning of dynamic systems. Robots and other autonomous machines use models of the real world to predict the result of their actions and make decisions, but existing methods used for machine-learning are unreliable in many cases and can be easily fooled. This project aims to make machine-learning of dynamic system models reliable, accurate, and secure. The outcomes of this project will be new models and algorithms that ensure safety and increase accuracy of models learned from data. This project will benefit robotics, control engineering, infrastructure automation, and other fields that demand the capability to model physical systems from limited data. It will also improve cybersecurity by making learning algorithms resilient to deliberate attacks with false data.Read moreRead less
New techniques to detect fetal heart abnormalities. Australia’s national fetal death rate is 6.7 per one thousand births. In Australia’s Indigenous community it surges to 12.3 deaths per one thousand births. Early diagnosis (and management) of abnormal fetu.ses with cardiac defects will go a long way in reducing these numbers. The proposed technology will help set up easy-to-use systems for fetal cardiac abnormality screening and reduce fetal deaths and congenital heart disease burden in adult l ....New techniques to detect fetal heart abnormalities. Australia’s national fetal death rate is 6.7 per one thousand births. In Australia’s Indigenous community it surges to 12.3 deaths per one thousand births. Early diagnosis (and management) of abnormal fetu.ses with cardiac defects will go a long way in reducing these numbers. The proposed technology will help set up easy-to-use systems for fetal cardiac abnormality screening and reduce fetal deaths and congenital heart disease burden in adult life. This project will also provide domain trained researchers with cutting edge international academic and industry expertise.Read moreRead less
Readying Wireless Networks for Future Communications Systems: From Ubiquitous Computing to the Internet of Things. This project aims to prepare wireless networks for future communications systems, by improving the data transmission rates of wireless networks, through developing new coding schemes based on the synergy of noisy-channel coding and index coding. This will allow wireless networks, used in conjunction with the fibre-optic National Broadband Network, to support future high-data-rate an ....Readying Wireless Networks for Future Communications Systems: From Ubiquitous Computing to the Internet of Things. This project aims to prepare wireless networks for future communications systems, by improving the data transmission rates of wireless networks, through developing new coding schemes based on the synergy of noisy-channel coding and index coding. This will allow wireless networks, used in conjunction with the fibre-optic National Broadband Network, to support future high-data-rate and ubiquitous communication services. This project aims to produce new theoretical results in the field of communication theory, and efficient practical coding schemes for wireless communications.Read moreRead less
Geomechanics of multiple seam mining interactions. This project will address a highly significant and timely problem that has arisen in the coal mining industry. Through the application of scientific principles and advanced methods of engineering analysis, this research will develop practical guidelines that in turn will provide the means for rational planning of multi-seam mining operations.
Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings a ....Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings and outcomes of this research will advance the knowledge and practice of hard-rock mining machines in Australia. The success of this project will significantly increase mining productivity and reduce human injuryRead moreRead less
A multi-scale theory of unsaturated porous media under extreme loading. Extreme loading induced by impacts, explosives or earthquakes generates stress wave propagation through unsaturated media; this can lead to rock fracturing and soil liquefaction and severely damage civil, mining and military infrastructures and operations. The project aims to develop a novel experimentally-validated theory, with associated models, for describing dynamic responses of unsaturated porous media subject to extrem ....A multi-scale theory of unsaturated porous media under extreme loading. Extreme loading induced by impacts, explosives or earthquakes generates stress wave propagation through unsaturated media; this can lead to rock fracturing and soil liquefaction and severely damage civil, mining and military infrastructures and operations. The project aims to develop a novel experimentally-validated theory, with associated models, for describing dynamic responses of unsaturated porous media subject to extreme loading. Our continuum framework will allow building constitutive models directly from saturation-dependent contact laws at the micro-scale. This will remove the need to use the site-dependent empirical models and thus give the derived constitutive models truly predictive capabilities.Read moreRead less