Industrial Transformation Training Centres - Grant ID: IC140100022
Funder
Australian Research Council
Funding Amount
$2,148,935.00
Summary
ARC Training Centre for Portable Analytical Separation Technologies. ARC Training Centre for Portable Analytical Separation Technologies. Portable analytical separation systems will enable point-of sample analysis for complex samples in food, environmental and clinical applications. The Training Centre aims to train the next generation of industry-ready Australian researchers through creating a sustainable research partnership between university-based researchers and Australian industry focused ....ARC Training Centre for Portable Analytical Separation Technologies. ARC Training Centre for Portable Analytical Separation Technologies. Portable analytical separation systems will enable point-of sample analysis for complex samples in food, environmental and clinical applications. The Training Centre aims to train the next generation of industry-ready Australian researchers through creating a sustainable research partnership between university-based researchers and Australian industry focused on developing new capabilities and technologies that have the potential to facilitate, support, or catalyse the progressive deployment of portable separation science technologies into society. This will enable the development of new, portable and affordable analytical separation systems and contribute to creating a sustainable, globally competitive manufacturing industry in Australia.Read moreRead less
Using data mining methods to remove uncertainties in sensor data streams. This project will develop key techniques for removing uncertainties in sensor data streams and thus improve the monitoring quality of sensor networks. The expected outcomes will benefit Australia by enabling improved, lower-cost monitoring of natural resources and management of stock raising.
Lectin based open tubular micro-reactors for probing protein-protein binding. This project seeks to develop non-invasive technology for the measurement and quantitation of lectin-carbohydrate binding events, in the first instance glycopeptides and glycoproteins. The goal is not only to provide accurate protein-protein association and dissociation constant data within the developed system, but to do so within an enclosed micro-fluidic environment, with the added advantages of also providing ‘trap ....Lectin based open tubular micro-reactors for probing protein-protein binding. This project seeks to develop non-invasive technology for the measurement and quantitation of lectin-carbohydrate binding events, in the first instance glycopeptides and glycoproteins. The goal is not only to provide accurate protein-protein association and dissociation constant data within the developed system, but to do so within an enclosed micro-fluidic environment, with the added advantages of also providing ‘trap and release’ extraction capabilities, and being easily coupled to both chromatographic and mass spectrometry systems. Read moreRead less
Miniaturised electrophoretic systems for distributed environmental sensing. This project aims to develop new low-cost sensors to quantify a range of water nutrients for continuous automated water monitoring. The project aims to design a microfluidic cartridge to obtain a particulate-free sample for analysis by the rapid separation of inorganic anions and cations. The cartridge is intended to be operated in a portable low cost, low weight, low power instrument. The deployment of multiple units ai ....Miniaturised electrophoretic systems for distributed environmental sensing. This project aims to develop new low-cost sensors to quantify a range of water nutrients for continuous automated water monitoring. The project aims to design a microfluidic cartridge to obtain a particulate-free sample for analysis by the rapid separation of inorganic anions and cations. The cartridge is intended to be operated in a portable low cost, low weight, low power instrument. The deployment of multiple units aims to provide a continuous data stream describing the changes in nutrient profiles within various waters, to feed into environmental models and inform best practice for agriculture and aquaculture industries.Read moreRead less
Portable and field-deployable analytical platforms for water monitoring. This project sets out to tackle one of the costliest and most challenging environmental problems, namely, nutrient pollution in water systems. At present, nutrient pollutant monitoring is predominantly carried out using an antiquated manual approach with numerous shortcomings, inadequate to achieve truly effective water quality management. The in-situ analyser developed and deployed within this project will provide continuo ....Portable and field-deployable analytical platforms for water monitoring. This project sets out to tackle one of the costliest and most challenging environmental problems, namely, nutrient pollution in water systems. At present, nutrient pollutant monitoring is predominantly carried out using an antiquated manual approach with numerous shortcomings, inadequate to achieve truly effective water quality management. The in-situ analyser developed and deployed within this project will provide continuous real-time observations and will allow users to remotely monitor water quality; alerting them to pollutant levels, enabling immediate action to be taken to prevent environmental damage. The system is low-cost, facilitating mass adoption, yet delivers an analytical performance comparable to leading laboratory analysers. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less
Ring constructions and algorithms for enhancing performance of BCH codes. BCH codes form a major class of codes used in modern communication systems. The aim of this project is to enhance the efficiency of this class of codes by combining them in constructions enabling correction of deletion and insertion errors, and develop efficient implementations of encoding and decoding algorithms incorporating soft decision methods for enhanced error correction. Significance of the project is explained by ....Ring constructions and algorithms for enhancing performance of BCH codes. BCH codes form a major class of codes used in modern communication systems. The aim of this project is to enhance the efficiency of this class of codes by combining them in constructions enabling correction of deletion and insertion errors, and develop efficient implementations of encoding and decoding algorithms incorporating soft decision methods for enhanced error correction. Significance of the project is explained by the role of fast, secure and reliable communications in modern information and communication technology. Expected outcomes include new efficient algorithms and commercial modules available for symbolic computation systems with applications in telecommunications industry.
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Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar ....Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH180100002
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. Thes ....ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. These dynamic systems will help determine what goal to achieve and the most efficient plan to achieve it. This Hub is expected to contribute to higher farming efficiency, lower production costs and fewer disease risks, giving the Australian industry new business opportunities and an international competitive advantage.Read moreRead less
Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching f ....Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching for ecological patterns on a national scale that would be difficult to identify using traditional approaches tuned to process-scale studies. Australian society stands to benefit by virtue of improved large-scale models of ecosystem function and reduced cost for conducting marine ecosystem investigations.Read moreRead less