Probing microbial emulsions to break barriers to green oil production. This project aims to understand ultrasonic processing of concentrated slurries of oil-bearing yeast and algae. Humans must reduce their dependency on petroleum. While microorganisms can produce oils as replacement fuels and base chemicals, the processes for extracting these oils are inefficient. Ultrasound could improve oil recovery by replacing toxic solvents. Understanding the effects of ultrasound on microbial emulsions is ....Probing microbial emulsions to break barriers to green oil production. This project aims to understand ultrasonic processing of concentrated slurries of oil-bearing yeast and algae. Humans must reduce their dependency on petroleum. While microorganisms can produce oils as replacement fuels and base chemicals, the processes for extracting these oils are inefficient. Ultrasound could improve oil recovery by replacing toxic solvents. Understanding the effects of ultrasound on microbial emulsions is expected to develop solvent-free oil recovery processes that improve the economic and environmental benefits of microbial oil production. Such processes would greatly increase the efficiency and reduce the cost of producing microbial oils that can be used as green alternatives to petroleum fuels and chemicals.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Maximising Bioenergy Recovery from Sewage Sludge. Sewage treatment is producing large amounts of sewage sludge, which represents a substantial, but largely untapped, energy source. This project aims to develop and demonstrate an innovative, economically attractive and environmentally friendly technology, and the underpinning science, to maximize bioenergy recovery from sewage sludge. The technology is based on the treatment of sludge using free ammonia, a by-product of sewage treatment. This pro ....Maximising Bioenergy Recovery from Sewage Sludge. Sewage treatment is producing large amounts of sewage sludge, which represents a substantial, but largely untapped, energy source. This project aims to develop and demonstrate an innovative, economically attractive and environmentally friendly technology, and the underpinning science, to maximize bioenergy recovery from sewage sludge. The technology is based on the treatment of sludge using free ammonia, a by-product of sewage treatment. This project is expected to benefit Australia by substantially reducing the reliance on fossil fuels and accelerating a shift to affordable renewable energy. The outcomes of the project would provide significant energy, economic, environmental and social benefits for Australians. Read moreRead less
Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve s ....Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve speed of operation, and reduce the cost and time of data acquisition and processing. Many applications are expected to benefit from this research including search and rescue, surveillance, security, and defence. The research outcomes are expected to enhance the capabilities of the Australian armed forces, counter-terrorism, police and law-enforcement agencies.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101297
Funder
Australian Research Council
Funding Amount
$429,000.00
Summary
A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the e ....A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the emerging field of biological imaging and to deliver an integrated imaging platform for mapping various tissue microscopic components at the cellular level. Successful outcomes have the potential for commercialisation and will accelerate a range of fundamental science and engineering studies requiring imaging techniques.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130101168
Funder
Australian Research Council
Funding Amount
$364,900.00
Summary
Enhancement of light-driven electricity generation by cyanobacteria: en route to biosolar panels. Some species of naturally occurring cyanobacteria (blue-green algae) exhibit a special metabolic feature, which enables them to convert sunlight into electricity. This project will unveil the chemical and biological secrets behind this process and will lead to the creation of the first entirely biological solar panel.
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
Sustainable wastewater management. This project aims to extract high-value liquid products (medium-chain fatty acids) from wastewater with minimised greenhouse gas emissions and energy consumption, in addition to clean water. Traditional wastewater treatment removes organic carbon and nutrients by using vast amounts of energy and releasing greenhouse gas. However, wastewater is a substantial but largely untapped renewable resource. The intended outcome is to transform wastewater from a troubleso ....Sustainable wastewater management. This project aims to extract high-value liquid products (medium-chain fatty acids) from wastewater with minimised greenhouse gas emissions and energy consumption, in addition to clean water. Traditional wastewater treatment removes organic carbon and nutrients by using vast amounts of energy and releasing greenhouse gas. However, wastewater is a substantial but largely untapped renewable resource. The intended outcome is to transform wastewater from a troublesome pollutant to a valuable resource and reduce carbon footprints.Read moreRead less
Novel concepts for bioelectrochemical generation of renewable fuels and chemicals from wastewater. Global warming and the diminishing fossil fuel resources are posing an ever increasing threat to our societies and economies. This project aims to develop novel and highly innovative bioelectrochemical processes for the production of valuable fuels and chemicals from wastewater, which is a largely untapped renewable resource.
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