The study of wear debris using advanced technologies. A large portion of the operating cost of machinery is associated with wear due to the interaction between moving surfaces, which generates wear particles as by-products. The wear particles thus carry information regarding the wearing process, and can be used to assess the machine's condition and further facilitate failure prediction and minimise maintenance. This project will explore the mechanisms and possible influence of corrosion on the w ....The study of wear debris using advanced technologies. A large portion of the operating cost of machinery is associated with wear due to the interaction between moving surfaces, which generates wear particles as by-products. The wear particles thus carry information regarding the wearing process, and can be used to assess the machine's condition and further facilitate failure prediction and minimise maintenance. This project will explore the mechanisms and possible influence of corrosion on the wearing process. A new methodology will be developed to quantify the wearing process. This research will significantly advance our understanding with respect to wear and provide innovative means for identifying wear mechanisms/phases.Read moreRead less
Qualitative and quantitative modelling of hydraulic fracturing of brittle materials. Few technologies have caused more concern in the general population than the so called hydraulic fracturing technique, applied to enhance the hydraulic conductivity of resource-bearing rocks by injecting high pressure fluids. The concern revolves around uncertainty with leakage of used chemicals to overlying aquifers, unwanted seismic events and surface subsidence. This research, combining experimental and compu ....Qualitative and quantitative modelling of hydraulic fracturing of brittle materials. Few technologies have caused more concern in the general population than the so called hydraulic fracturing technique, applied to enhance the hydraulic conductivity of resource-bearing rocks by injecting high pressure fluids. The concern revolves around uncertainty with leakage of used chemicals to overlying aquifers, unwanted seismic events and surface subsidence. This research, combining experimental and computational investigations, aims to establish fundamental understanding of key processes controlling fracture formation in brittle materials (coal seams and porous rocks) under the action of hydraulic fracturing. The research outcomes will help to assess and minimise the risks associated with the hydraulic fracturing technology. Read moreRead less
The Influence of particle shape fragmentation and compaction on 3D hopper flow. According to world-leading material scientist Patrick Richard, "Granular materials are ubiquitous in nature and are the second-most manipulated material in industry (the first one is water)". Our research will produce massive three dimensional computer simulations predicting and analysing the influence of particle size and shape on the morphology of industrial and natural granular flows. The results will have directl ....The Influence of particle shape fragmentation and compaction on 3D hopper flow. According to world-leading material scientist Patrick Richard, "Granular materials are ubiquitous in nature and are the second-most manipulated material in industry (the first one is water)". Our research will produce massive three dimensional computer simulations predicting and analysing the influence of particle size and shape on the morphology of industrial and natural granular flows. The results will have directly and immediately relevant applications in a range of Australian industries, including mass mining and minerals processing and will further make a major contribution to understanding and modelling a variety of geo-hazards.
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Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make th ....Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make the speech and speaker recognition systems less sensitive to additive background noise and make them more useful in telecommunications and business.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
Flotation in high salt concentration: resolving critical knowledge gaps relating the ion effect on bubble production and behavior. Flotation separation of coal and mineral particles by attaching to rising air bubbles is significantly affected in high salt concentration but its exact mechanism still remains unclear. This project employs state-of-the-art surface sensitive spectroscopy and modeling tools to investigate how salt ions influence drainage and rupture of liquid films between two bubbles ....Flotation in high salt concentration: resolving critical knowledge gaps relating the ion effect on bubble production and behavior. Flotation separation of coal and mineral particles by attaching to rising air bubbles is significantly affected in high salt concentration but its exact mechanism still remains unclear. This project employs state-of-the-art surface sensitive spectroscopy and modeling tools to investigate how salt ions influence drainage and rupture of liquid films between two bubbles, and bubble production and behaviour relevant to the flotation processes. The research will develop better water use for coal and mineral flotation to reduce reagent usage and environmental impacts of water pollution. The project will contribute significantly to knowledge advancement in the coal and mineral industry.Read moreRead less
A new role for vibration analysis in gear wear modelling and prediction. This project aims to improve prediction of the remaining useful life of gears. Gears are widely used in industry and transport. This project aims to integrate the two main methods of gear condition monitoring, vibration and oil analysis, and perform model-based wear prediction with the tribology and dynamic models continually updated on the basis of measured wear debris and vibration. New signal processing tools should allo ....A new role for vibration analysis in gear wear modelling and prediction. This project aims to improve prediction of the remaining useful life of gears. Gears are widely used in industry and transport. This project aims to integrate the two main methods of gear condition monitoring, vibration and oil analysis, and perform model-based wear prediction with the tribology and dynamic models continually updated on the basis of measured wear debris and vibration. New signal processing tools should allow estimation of relatively weak friction forces, previously neglected, as an important prognostic tool. This would allow detailed root cause analysis and prediction of remaining useful life. Improvements in gear prognosis would have safety and economic benefits by eliminating unforeseen catastrophic failures and optimising maintenance schedules.Read moreRead less
Embracing Changes for Responsive Video-sharing Services. Video-sharing platforms are a critical information channel for the public. Increasing scale and shifts in user base, with Generation Z now as the dominant user, have resulted in an unprecedented amount of ubiquitous changes in the content and users of these platforms which greatly challenges the responsiveness and quality of the services provided. This project aims to design innovative algorithms to effectively predict and leverage changes ....Embracing Changes for Responsive Video-sharing Services. Video-sharing platforms are a critical information channel for the public. Increasing scale and shifts in user base, with Generation Z now as the dominant user, have resulted in an unprecedented amount of ubiquitous changes in the content and users of these platforms which greatly challenges the responsiveness and quality of the services provided. This project aims to design innovative algorithms to effectively predict and leverage changes, optimise the value of changes, and extract insights from changes for diverse downstream applications of video-sharing platforms. The expected outcomes will create new-generation representation learning techniques, and provide practical tools to amplify the socioeconomic values of video-sharing platforms.Read moreRead less
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
Bio-electrochemical sulfate reduction and sulfur recovery without external carbon source. Highly acidic waterways and mining wastewaters create major environmental challenges in inland Australia. This project will use novel, solar driven biological processes to remove the acid and metals from these streams and enable beneficial reuse of the water and other resources recovered in the process.