Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Enabling wider use of mechanistic models for biodiversity forecasts . Forecasting species distributions is challenging yet necessary. The pattern-based models commonly used are error-prone. Mechanistic models, best equipped for the task, are limited by lack of data. This project aims to enable wider use of mechanistic models by developing new methods for dealing with incomplete trait data and uncertainty. It expects to generate new knowledge about how species’ traits define the environments in w ....Enabling wider use of mechanistic models for biodiversity forecasts . Forecasting species distributions is challenging yet necessary. The pattern-based models commonly used are error-prone. Mechanistic models, best equipped for the task, are limited by lack of data. This project aims to enable wider use of mechanistic models by developing new methods for dealing with incomplete trait data and uncertainty. It expects to generate new knowledge about how species’ traits define the environments in which they persist. Anticipated outcomes include enhanced capacity to apply mechanistic models to conservation problems, methods for communicating uncertainties and models for tens of species of immediate conservation interest. This will enable more reliable biodiversity forecasts, supporting better decision-making.
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Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in mi ....Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in microscale tissue properties are lacking. The tools developed by this project will be used to generate new magnetic resonance image based maps to convey information on tissue microstructure changes in the human brain. Additionally, the mathematical tools developed will be transferable to other applications where diffusion and transport in heterogeneous porous media play a role.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH210100051
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
The ARC Research Hub for Digital Bioprocess Development. The ARC Hub for Digital Bioprocess Development aims to assist the Biopharma industry by increasing digital innovation, productivity and competitiveness. An interdisciplinary team of engineers, scientists and computing specialists will develop digitally integrated advanced manufacturing processes and a platform for industry adoption. The program will address key bioprocessing research challenges and develop new process and digital models th ....The ARC Research Hub for Digital Bioprocess Development. The ARC Hub for Digital Bioprocess Development aims to assist the Biopharma industry by increasing digital innovation, productivity and competitiveness. An interdisciplinary team of engineers, scientists and computing specialists will develop digitally integrated advanced manufacturing processes and a platform for industry adoption. The program will address key bioprocessing research challenges and develop new process and digital models that can predict and optimise manufacturing processes, resulting in greater yields, faster and more flexible processes and enhanced product stability. The Hub will transform biopharmaceutical manufacturing and unlock growth opportunities to forge an internationally competitive Australian Biopharma sector.Read moreRead less
Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expect ....Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expected outcomes include protocol to accurately monitor emissions, models to predict emission under various conditions, and mitigation guideline for typical plant configurations. The anticipated benefit is a significant reduction in GHG emissions from urban water industry and support it to meet net-zero-emission goal by 2050.Read moreRead less
Sewer corrosion reduction through model-supported ventilation control. Ventilation is one of the key technologies for sewer corrosion control. However, its design and operation are currently based on experience and empirical equations, often leading to unsatisfactory results. By integrating in-depth laboratory and pilot-sewer studies under defined conditions with extensive field investigations, this multidisciplinary project aims to develop critical models to predict the corrosion process in res ....Sewer corrosion reduction through model-supported ventilation control. Ventilation is one of the key technologies for sewer corrosion control. However, its design and operation are currently based on experience and empirical equations, often leading to unsatisfactory results. By integrating in-depth laboratory and pilot-sewer studies under defined conditions with extensive field investigations, this multidisciplinary project aims to develop critical models to predict the corrosion process in response to ventilation and dynamic wastewater and atmospheric conditions, enabling model-based sewer ventilation design and operation. The project also aims to deliver novel, field-demonstrated ventilation strategies. The project findings will be incorporated in the Australian ventilation design and operation guidelines.Read moreRead less
Multilayer Graphene Based Anti-Corrosion Polymer Coated Structures. This project aims to develop a novel multilayer graphene/polymer coating for structures exposed to corrosive environment with graphene concentration varying layer-wise to eliminate galvanic corrosion yet maintain all unique advantages owing to graphene inclusion, thus offering a cost-effective design solution with significantly improved anti-corrosion performance and remarkably enhanced safety and durability for structures. Expe ....Multilayer Graphene Based Anti-Corrosion Polymer Coated Structures. This project aims to develop a novel multilayer graphene/polymer coating for structures exposed to corrosive environment with graphene concentration varying layer-wise to eliminate galvanic corrosion yet maintain all unique advantages owing to graphene inclusion, thus offering a cost-effective design solution with significantly improved anti-corrosion performance and remarkably enhanced safety and durability for structures. Expected outcomes of this project include an innovative design, experimental data on corrosion prevention, development of reliable simulation techniques and design procedures for the proposed coating. This should provide huge benefits to Australian civil, offshore and marine engineering industry and national economy.Read moreRead less