Advanced Materials from Automated Synthesis of Sequence-Defined Polymers. The project aims to develop industrially scalable and environmentally friendly methods for synthesis of sequence-defined multiblock copolymers (polymer chains containing segments of different polymer types) using automated synthesis methods. The materials to be explored will be largely based on renewable biomass-derived monomeric building blocks. Such polymers are able to undergo microphase separation into spatially period ....Advanced Materials from Automated Synthesis of Sequence-Defined Polymers. The project aims to develop industrially scalable and environmentally friendly methods for synthesis of sequence-defined multiblock copolymers (polymer chains containing segments of different polymer types) using automated synthesis methods. The materials to be explored will be largely based on renewable biomass-derived monomeric building blocks. Such polymers are able to undergo microphase separation into spatially periodic compositional patterns, thereby providing access to a vast range of nano-engineered materials. This would enable design and synthesis of new advanced materials, making use of renewable resources and supporting the circular economy, with diverse potential applications ranging from nanomedicine to materials science.Read moreRead less
Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applicatio ....Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applications of significant social, environmental and economic value, such as Location-Aware Service, Environment Monitoring, Augmented Reality, Autonomous Vehicle, and Rapid Emergency Response. The project will enhance Australia's international competitive advantage in forefront of ICT research and technology innovation.Read moreRead less
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
Clarence River Green Prawn Market Diversification Assistance Measures
Funder
Fisheries Research and Development Corporation
Funding Amount
$165,000.00
Summary
The Clarence River Region is known for its high-quality prawn markets. The region was kept profitable during COVID restrictions due to a significant portion of the fisher directing its product to the highly profitable bait market. This diversification away from the consumer market has ensured stability for the region. Many fishing businesses pivoted their strategies to meet this new buyer to the region. The loss of the uncooked prawn market in the Clarence region will therefore destabilize t ....The Clarence River Region is known for its high-quality prawn markets. The region was kept profitable during COVID restrictions due to a significant portion of the fisher directing its product to the highly profitable bait market. This diversification away from the consumer market has ensured stability for the region. Many fishing businesses pivoted their strategies to meet this new buyer to the region. The loss of the uncooked prawn market in the Clarence region will therefore destabilize the industry. The restriction of uncooked prawn trade therefore must be addressed through market research, diversification and activation. However, there is immediate need for alternative markets so an intense focused market activation and access is the key. PFA has identified key market persons that can create links between industry and high-end chefs to: 1. Identify alternative market uses that fall within the quarantine requirements 2. Start immediate market trials and activation 3. Review online presence and build industry skills to improve online presence for sales • It is intended that this will lead into immediate supply agreements to these alternative markets that will in turn remove burden on the existing cooked prawn market
Objectives: 1. To identify and trial supplies of Clarence River prawns to alternative market 2. To activate alternative markets to reduce negative impact of trade restriction to the Clarence River region 3. To build skills within local fishers to build online presence Read moreRead less
A Midas touch for electrophiles in new reaction development. This project aims to address the lack of knowledge about how high-value organic molecules are formed in gold-catalysed reactions by advancing a novel mode of catalysis. This project expects to generate new knowledge about these gold-catalysed reactions using an innovative, interdisciplinary approach incorporating computational and synthetic techniques. Expected outcomes of this project include the optimisation and development of import ....A Midas touch for electrophiles in new reaction development. This project aims to address the lack of knowledge about how high-value organic molecules are formed in gold-catalysed reactions by advancing a novel mode of catalysis. This project expects to generate new knowledge about these gold-catalysed reactions using an innovative, interdisciplinary approach incorporating computational and synthetic techniques. Expected outcomes of this project include the optimisation and development of important organic reactions and enhancing collaboration nationally and internationally between computational and synthetic chemists. This should provide significant benefits in the form of improved chemical reactions for chemists to prepare new pharmaceuticals, agrochemicals and materials.Read moreRead less
Declarative Networks: Towards Robust and Explainable Deep Learning. The aim of this project is to develop declarative machine learning techniques that exploit inherent structure and models of the world. Deep learning has become the dominant approach for machine learning with many products and promises built on this technology. But deep learning is expensive, opaque, brittle and relies solely on human labelled data. This project intends to make deep learning more reliable by establishing theory a ....Declarative Networks: Towards Robust and Explainable Deep Learning. The aim of this project is to develop declarative machine learning techniques that exploit inherent structure and models of the world. Deep learning has become the dominant approach for machine learning with many products and promises built on this technology. But deep learning is expensive, opaque, brittle and relies solely on human labelled data. This project intends to make deep learning more reliable by establishing theory and algorithms that allow physical and mathematical models to be embedded within a deep learning framework, providing performance guarantees and interpretability. This would likely benefit machine learning based products that can understand the world and interact with humans naturally through vision and language.Read moreRead less
Switchable and stereocontrolled photoredox catalysis. This project aims to develop new catalytic synthetic reactions for the rapid and more direct functionalisation of organic compounds under mild conditions with the use of visible light. An integrated experimental and computational approach will be used to design potent visible-light photocatalysts that retain the advantages of standard photoredox catalysis but with the added ability to intercept and, thus control, reactive intermediates in sit ....Switchable and stereocontrolled photoredox catalysis. This project aims to develop new catalytic synthetic reactions for the rapid and more direct functionalisation of organic compounds under mild conditions with the use of visible light. An integrated experimental and computational approach will be used to design potent visible-light photocatalysts that retain the advantages of standard photoredox catalysis but with the added ability to intercept and, thus control, reactive intermediates in situ. This will enable the control of stereochemistry in photoredox reactions – not possible with standard catalysts - and establish other useful synthetic transformations. These strategies will make it easier to prepare valuable classes of organic molecules – efficiently, safely, and cost-effectively.
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Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces an ....Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces and system dynamics. Both theoretical and algorithmic approaches will be applied to sustainable fishery management --- an important problem for Australia and an ideal context for POMDPs. The project will advance research in artificial intelligence, dynamical systems, and fishery operations, and benefit the national economy.Read moreRead less
Improving Southern Rock Lobster On-vessel Handling Practices, Data Collection And Industry Tools For Lobster Quality Assessment
Funder
Fisheries Research and Development Corporation
Funding Amount
$538,604.00
Summary
The export of Southern Rock Lobster (SRL) from Southern Australia to international markets is one of Australia's most valuable fisheries. There are increasing trends in post-harvest mortality of SRL confirmed by the recent Fisheries Research and Development Corporation project (FRDC 2016-235). This is costing the industry millions due to stock losses, decreased consumer confidence in product quality and reputational damage to the SRL market brand. The causes of this increased post-harvest mortal ....The export of Southern Rock Lobster (SRL) from Southern Australia to international markets is one of Australia's most valuable fisheries. There are increasing trends in post-harvest mortality of SRL confirmed by the recent Fisheries Research and Development Corporation project (FRDC 2016-235). This is costing the industry millions due to stock losses, decreased consumer confidence in product quality and reputational damage to the SRL market brand. The causes of this increased post-harvest mortality are inconsistent across the industry sector with a range of factors implicated including environmental stressors, novel health conditions, and sub-optimal post-harvest practices. Results from (FRDC2016-235) indicate a need to optimise live lobster management processes across the entire post-harvest chain of custody in-order to minimize lobster mortality and enhance the economics of the SRL fishing and processing industry sectors.
The FRDC SRL live holding project (2016-235) conducted an analysis of the processing industry sector practices and provided guidance for best practices. These recommendations have been welcomed by the industry and further consultation has identified a critical need to extend this approach to the fishing component of the industry.
This project will address these key industry priorities and conduct an analysis of on-vessel live lobster handling and holding practices, quantify the impact of systems and practices on lobster quality and provide recommendations on improving on-vessel post-harvest practices. The current FRDC traceability project (FRDC 2016-177) is trialing a range of traceability technologies that this proposed new project will extend and enhance on-vessels to strengthen the capture, monitoring, and analysis of post-harvest data on lobster welfare, quality, and handling practices.
This project will also extend the development of practical and easy to use tools for the evaluation of lobster health including the handheld lactate meter and refractive index. Building evidenced-based approaches to measuring health and stress will provide all industry sectors with improved measurement of quality, animal welfare, and sustainability at all points in the supply chain.
Objectives: 1. Investigate the impacts of on-vessel handling and maintenance practices on live SRL post-harvest performance 2. Develop practical tools for the improved management of SRL industry live lobster operations (ie hand-held lactate meter and refractive index including thresholds for poor lobster performance) 3. Extend findings to the SRL industry (best practice guides and workshops) and incorporation of results into the SRL Clean green program. Read moreRead less