Tough bio-derived and biodegradable wood plastic composites. This project aims for the development of tough bio-based and biodegradable wood plastic composites (WPCs), directly addressing a key end-user demand that performance of bio-WPCs must be at least comparable with existing commercial WPCs. The project expects to generate key innovations such as developing a new, high performance, bio-based and biodegradable WPC by incorporating native spinifex-derived nano-cellulose fibres, ensuring excel ....Tough bio-derived and biodegradable wood plastic composites. This project aims for the development of tough bio-based and biodegradable wood plastic composites (WPCs), directly addressing a key end-user demand that performance of bio-WPCs must be at least comparable with existing commercial WPCs. The project expects to generate key innovations such as developing a new, high performance, bio-based and biodegradable WPC by incorporating native spinifex-derived nano-cellulose fibres, ensuring excellent, molecular-level dispersion with a novel low-cost and energy-efficient wet-mix technology. This will provide significant benefits as it will lead to new products and markets for the Australian forestry industry and for rural and indigenous Australia, maximising Australia’s competitive advantage in biomass-derived products.Read moreRead less
Nanoengineered, Encapsulated Catalysts from Fly Ash Waste. This project aims to deliver advanced catalysts and novel catalyst synthesis methods from the use of iron-rich fly ash, an otherwise abundant valueless waste with projected steady growth across Australia and globally. The as-synthesised catalysts are expected to be applicable to and exhibit excellent activity in the production of green hydrogen and renewable bio-fuels from lignocellulosic waste. These efforts are significant and benefici ....Nanoengineered, Encapsulated Catalysts from Fly Ash Waste. This project aims to deliver advanced catalysts and novel catalyst synthesis methods from the use of iron-rich fly ash, an otherwise abundant valueless waste with projected steady growth across Australia and globally. The as-synthesised catalysts are expected to be applicable to and exhibit excellent activity in the production of green hydrogen and renewable bio-fuels from lignocellulosic waste. These efforts are significant and beneficial in restoring the manufacturing capability of Australian industry, driving Australian industry towards the development of a circular economy for the appropriate management of solid waste, as well as for a seamless introduction of renewable and clean energy sources to address the pressing climate change.Read moreRead less
Robust Automatic Speaker Diarisation of Audio Documents by Exploiting Prior Sources of Information. Speaker Diarisation, the task of determining who spoke when, is a technology fundamental in deriving intelligent information from audio and multimedia resources. The requirement for efficient and accurate Speaker Diarisation systems, portable across different domains is heightened by the explosive growth of audio and multimedia archives online and throughout the world. This research will provide t ....Robust Automatic Speaker Diarisation of Audio Documents by Exploiting Prior Sources of Information. Speaker Diarisation, the task of determining who spoke when, is a technology fundamental in deriving intelligent information from audio and multimedia resources. The requirement for efficient and accurate Speaker Diarisation systems, portable across different domains is heightened by the explosive growth of audio and multimedia archives online and throughout the world. This research will provide the foundation for a commercial service of automatic Speaker Diarisation to be developed, growing Australia's impact on the information and communications technology (ICT) sector. The outcome of this research will also assist in the tracking of terrorist and unlawful activity by enabling effective intelligence gathering from different audio sources.Read moreRead less
Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament ....Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament tears in sporting injuries and other traumas.
The software developed will be provided on the project’s partner (Siemens) platform and will therefore be available worldwide and have a consequently large impact on the field.
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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
Biosolid flow, separation and activity in anaerobic lagoons. This project aims to develop a fundamental model of the complex, non-steady state flow behaviour in anaerobic lagoons. The project will develop new operating procedures and designs for large municipal, industrial and agricultural anaerobic lagoons. This will improve the efficiency of anaerobic digestion and reduce wastewater treatment costs, as well as increase renewable and sustainable biogas production. The intended outcome is a va ....Biosolid flow, separation and activity in anaerobic lagoons. This project aims to develop a fundamental model of the complex, non-steady state flow behaviour in anaerobic lagoons. The project will develop new operating procedures and designs for large municipal, industrial and agricultural anaerobic lagoons. This will improve the efficiency of anaerobic digestion and reduce wastewater treatment costs, as well as increase renewable and sustainable biogas production. The intended outcome is a validated 3D model that captures the physical and biological complexities of anaerobic lagoons. This will impact the design and operation of partner organisation lagoons, reducing capital and operating costs and improving biogas production.Read moreRead less
The next generation speaker recognition system. The next generation of speaker recognition technologies developed through this project will enable secure person authentication by voice in financial transactions and benefit the community through the elimination of identity fraud. This project will safeguard Australia by identifying criminal suspects using their voice and combat terrorism by using voice to locate and track terrorists.
Progressive Transmission of Street Directory Assistance and Business Pages over 3G and 4G mobile networks. Multimedia on-demand and live services over 3G and 4G mobiles will be enhanced. New methods for low volume, high information transfer multimedia transactions will be developed. This will create new jobs in the Information and Communication Technologies (ICT) sector. Progressive transmission of street directory assistance and business pages information to mobile handsets will enable citize ....Progressive Transmission of Street Directory Assistance and Business Pages over 3G and 4G mobile networks. Multimedia on-demand and live services over 3G and 4G mobiles will be enhanced. New methods for low volume, high information transfer multimedia transactions will be developed. This will create new jobs in the Information and Communication Technologies (ICT) sector. Progressive transmission of street directory assistance and business pages information to mobile handsets will enable citizens to make efficient use of their time and improve productivity. The 3G and 4G cellular telephone network, extended with 'mobile' base stations and satellite links, are especially attractive to a large country like Australia. Interactive information retrieval will become more universal and not limited through wired Internet connections.
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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
Automatic audio segmentation, classification, identification, search and retrieval. The research aims to develop generic tools for automated audio segmentation, classification, identification and search, with lowest possible computational complexity and highest accuracy and speed. The tools will be applicable to audio archive management, search of audio material over WWW and personal archives of music and audio-assisted video analysis. The industry will use the tools for automated broadcast ve ....Automatic audio segmentation, classification, identification, search and retrieval. The research aims to develop generic tools for automated audio segmentation, classification, identification and search, with lowest possible computational complexity and highest accuracy and speed. The tools will be applicable to audio archive management, search of audio material over WWW and personal archives of music and audio-assisted video analysis. The industry will use the tools for automated broadcast verification and identification for copyright surveillance and calculation of royalty payments, aiming to penetrate both Australian and overseas markets. The area of real-time audio scene analysis is in its infancy and the research aims to make significant contributions to this area.Read moreRead less