Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
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
Computational modelling of nanofluids for industrial applications. The use of nanoparticles in heat transfer fluids, then known as nanofluids, increases their specific heat and thermal conductivity. Recent experimental works highlight that anomalous transport phenomena are evident in nanofluids that cannot be adequately described by classical conservation laws. We will extend these conservation laws to incorporate fractional operators to capture the fluid memory effects and the impact of particl ....Computational modelling of nanofluids for industrial applications. The use of nanoparticles in heat transfer fluids, then known as nanofluids, increases their specific heat and thermal conductivity. Recent experimental works highlight that anomalous transport phenomena are evident in nanofluids that cannot be adequately described by classical conservation laws. We will extend these conservation laws to incorporate fractional operators to capture the fluid memory effects and the impact of particle clustering. Computational modelling and experimental investigations will be undertaken to identify the heat transfer mechanisms of various nanofluids. The outcomes of the work will increase knowledge on nanofluids and offer a significant opportunity to improve the efficiency of many thermal engineering systems.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
The culture of implementing Freedom of Information in Australia. In partnership with three Australian Information Commissioners/Ombudsmen this project aims to map the culture of administering Freedom of Information (FOI) laws across a number of Australian jurisdictions. The study aspires to capture and analyse the attitudes among FOI practitioners, government agency managements and political leaders toward information access implementation. The project aims to provide the partner organisations w ....The culture of implementing Freedom of Information in Australia. In partnership with three Australian Information Commissioners/Ombudsmen this project aims to map the culture of administering Freedom of Information (FOI) laws across a number of Australian jurisdictions. The study aspires to capture and analyse the attitudes among FOI practitioners, government agency managements and political leaders toward information access implementation. The project aims to provide the partner organisations with an increased understanding of the culture of administering FOI to inform training/awareness programs and campaigns in order to increase the functionality of FOI. Well-functioning access to information systems is crucial both for good governance and Australia's participation in the digital economy.
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Managing the risks posed by Artificial General Intelligence. It is widely acknowledged that a failure to implement appropriate controls for the next generation of Artificial Intelligence, Artificial General Intelligence (AGI), could have catastrophic consequences, including in the worst case - the extinction of the human race. This research aims to forecast the risks associated with AGI systems and identify the controls required to ensure that risks and existential threats are minimised. The exp ....Managing the risks posed by Artificial General Intelligence. It is widely acknowledged that a failure to implement appropriate controls for the next generation of Artificial Intelligence, Artificial General Intelligence (AGI), could have catastrophic consequences, including in the worst case - the extinction of the human race. This research aims to forecast the risks associated with AGI systems and identify the controls required to ensure that risks and existential threats are minimised. The expected outputs will provide designers, organisations, regulators and governments with a framework to support the design, implementation, and management of safe and efficient AGI systems. This will ensure that the potential far-reaching benefits of AGI are realised without undue threat to society.Read moreRead less
Transforming tobacco policy to deliver societal benefits. This project aims to develop new regulatory options for tobacco to minimise the legal market while avoiding the adverse societal and economic impacts of transferring consumer demand to illegal tobacco products. It addresses a significant current concern about a growing illegal tobacco market and seeks to improve understanding of the impact of tobacco control policies on the illegal market, and the societal impacts. The project also seeks ....Transforming tobacco policy to deliver societal benefits. This project aims to develop new regulatory options for tobacco to minimise the legal market while avoiding the adverse societal and economic impacts of transferring consumer demand to illegal tobacco products. It addresses a significant current concern about a growing illegal tobacco market and seeks to improve understanding of the impact of tobacco control policies on the illegal market, and the societal impacts. The project also seeks to draw insights from illicit drug policy to understand potential consequences of greater restrictions on the legal tobacco market. The expected outcomes include an enhanced monitoring system for illicit tobacco and policy recommendations to achieve government goals of reducing smoking rates.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Stability Analysis of Power System with Massive Power Electronic Devices. The decarbonization of Australia's power systems is to integrate massive renewable energy sources which are interfaced with many power electronic devices (PEDs). The fast and complex dynamics of PEDs have significantly changed the nature of the power system, which limits the applicability of existing tools and methods to assess its stability. The goal of this project is to gain a comprehensive insight into the stability of ....Stability Analysis of Power System with Massive Power Electronic Devices. The decarbonization of Australia's power systems is to integrate massive renewable energy sources which are interfaced with many power electronic devices (PEDs). The fast and complex dynamics of PEDs have significantly changed the nature of the power system, which limits the applicability of existing tools and methods to assess its stability. The goal of this project is to gain a comprehensive insight into the stability of a futuristic power system with high penetration of PEDs. The intended outcomes will be a model and data jointly driven methodology for high-efficient and real-time stability assessment. The methodology developed in this project will support Australia's transition to a stable, secure, and low-carbon power grid.Read moreRead less
Emotions and Employee Turnover: New Methods for Complex Dynamic Systems. This project aims to vastly improve the data-analytic capabilities of social and health researchers, while increasing knowledge about emotion dynamics and their link to employee turnover. By drawing on and advancing methods from ecology and applied physics, this project plans to investigate the role that individual emotions play in employee turnover with new quantitative methods for characterising and testing causality in c ....Emotions and Employee Turnover: New Methods for Complex Dynamic Systems. This project aims to vastly improve the data-analytic capabilities of social and health researchers, while increasing knowledge about emotion dynamics and their link to employee turnover. By drawing on and advancing methods from ecology and applied physics, this project plans to investigate the role that individual emotions play in employee turnover with new quantitative methods for characterising and testing causality in complex dynamic systems. The expected outcomes include an improved capacity for researchers, managers, and policy makers to understand complex organisational, economic, and health systems. This will provide immediate societal benefits by informing the development and deployment of targeted interventions in such systems.Read moreRead less