Enhancing sensory perception and balance control in HMD-based VR. This project seeks to test a revolutionary new theoretical framework for understanding how we perceive our self-motion and maintain postural control when immersed in head-mounted display (HMD) virtual reality (VR). Photorealistic graphical simulations and artificial vestibular stimulation will be used to investigate how visual and non-visual information concerning self-motion is integrated in the brain. The outcomes will reveal ho ....Enhancing sensory perception and balance control in HMD-based VR. This project seeks to test a revolutionary new theoretical framework for understanding how we perceive our self-motion and maintain postural control when immersed in head-mounted display (HMD) virtual reality (VR). Photorealistic graphical simulations and artificial vestibular stimulation will be used to investigate how visual and non-visual information concerning self-motion is integrated in the brain. The outcomes will reveal how multisensory interaction influences our sensory perception and postural control during HMD VR. The knowledge gained is expected to generate new economic benefits by inspiring next-generation technologies that will optimise users' immersive experiences (e.g., virtual exploration and immersive gaming).Read moreRead less
Distributed Optimisation without Central Coordination. This project will develop the mathematical foundations for discovery and analysis of iterative methods for optimisation problems in distributed computing systems. Most methods in distributed optimisation were not designed for distributed computing, rather they were adapted for purpose post-hoc. By building on recent advances in monotone operator splitting, this project expects to develop a mathematical theory for decentralised optimisation a ....Distributed Optimisation without Central Coordination. This project will develop the mathematical foundations for discovery and analysis of iterative methods for optimisation problems in distributed computing systems. Most methods in distributed optimisation were not designed for distributed computing, rather they were adapted for purpose post-hoc. By building on recent advances in monotone operator splitting, this project expects to develop a mathematical theory for decentralised optimisation algorithms specially designed for distributed systems. The framework is expected to produce a suite of algorithms, each customised to exploit a specific network configuration. The project will provide significant benefits in distributed machine learning applications such as federated learning.Read moreRead less
Consumer and Community Involvement Process Implementation Model . The project aims to examine the barriers and enablers to Consumer and Community Involvement. We will generate new knowledge via innovative methods from narrative medicine and economic and marketing studies including establishing the first Community of Practice for consumers and stakeholders in dementia research as the example. The outcomes include the creation of a process implementation model for Consumer and Community Involvemen ....Consumer and Community Involvement Process Implementation Model . The project aims to examine the barriers and enablers to Consumer and Community Involvement. We will generate new knowledge via innovative methods from narrative medicine and economic and marketing studies including establishing the first Community of Practice for consumers and stakeholders in dementia research as the example. The outcomes include the creation of a process implementation model for Consumer and Community Involvement to inform policies and guidelines for research systems and funding. This process model will propel research forward and generate opportunities to maximise the health and social benefits of research, including significant translation of research into practice. Read moreRead less
Obstacles to Contract Enforcement in Indonesia. The Australia-Indonesia Comprehensive Economic Partnership (IA-CEPA) came into force in 2020 but foreign investment in Indonesia has consistently failed to meet targets, largely due to concerns about the lack of reliable and just judicial contract enforcement. This project aims to investigate why predictable and fair contract enforcement in Indonesia is so inaccessible, particularly for foreign investors, and, through doctrinal and empirical resear ....Obstacles to Contract Enforcement in Indonesia. The Australia-Indonesia Comprehensive Economic Partnership (IA-CEPA) came into force in 2020 but foreign investment in Indonesia has consistently failed to meet targets, largely due to concerns about the lack of reliable and just judicial contract enforcement. This project aims to investigate why predictable and fair contract enforcement in Indonesia is so inaccessible, particularly for foreign investors, and, through doctrinal and empirical research, explain the causes of this situation. In partnership with Indonesian courts and lawyers, it also aims to support the development of legal and policy reform proposals that can help resolve Indonesia’s commercial contract enforcement problems and encourage Australian investment there.Read moreRead less
Time consistency, risk-mitigation and partially observable systems. This project aims to find optimal decision rules that mitigate risk in a time consistent manner for partially observable systems. Many problems in conservation management and engineering systems are dependent on random environments and entail risk of failure. The challenge of consistently minimising such a risk while achieving satisfactory and sustainable resource consumption is considerable. This project aims to develop analyti ....Time consistency, risk-mitigation and partially observable systems. This project aims to find optimal decision rules that mitigate risk in a time consistent manner for partially observable systems. Many problems in conservation management and engineering systems are dependent on random environments and entail risk of failure. The challenge of consistently minimising such a risk while achieving satisfactory and sustainable resource consumption is considerable. This project aims to develop analytical and numerical methods for optimal control in such scenarios. These methods will have application to fishery management, communication networks, power systems and social resource allocation scenarios.Read moreRead less
Determining features that separate groups of protein sequences. This project aims to develop mathematical approaches for determining features that distinguish one group of proteins from another, based on their amino acid sequences. The groups of sequences will reflect different outcomes, so that identifying the fundamental features can result in targeted interventions against the poorer outcome. A simple comparison at each position or of known features can fail to determine robust differentiator ....Determining features that separate groups of protein sequences. This project aims to develop mathematical approaches for determining features that distinguish one group of proteins from another, based on their amino acid sequences. The groups of sequences will reflect different outcomes, so that identifying the fundamental features can result in targeted interventions against the poorer outcome. A simple comparison at each position or of known features can fail to determine robust differentiators and so more complex methods are required. The project will, for example, help identify HIV vaccine targets by comparing early HIV transmission sequences from those in chronic infection. The methods will be applicable to viral proteins where high mutation rates make this task even more complex.Read moreRead less
A unified approach to the design of minimum length networks. This project aims to develop a new approach to designing minimum length interconnection networks by analysing their geometric structure. These networks form the basis of communication, power and transport systems. Optimising the design of such networks is a mathematically challenging problem of high computational complexity. This project will use an innovative method based on a relationship between the geometry of networks and a type o ....A unified approach to the design of minimum length networks. This project aims to develop a new approach to designing minimum length interconnection networks by analysing their geometric structure. These networks form the basis of communication, power and transport systems. Optimising the design of such networks is a mathematically challenging problem of high computational complexity. This project will use an innovative method based on a relationship between the geometry of networks and a type of partitioning of the plane called an oriented Voronoi diagram. The outcome will be efficient new algorithms for designing physical networks, which, in practice, will ultimately lead to a reduction in network infrastructure costs for industries in Australia.
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Harnessing Business Insights from Unstructured Customer Data. Resulting from customers’ widespread uptake of online channels to buy and communicate has been a surge in online reviews and social media posts. This textual information offers a viable alternative to surveys that Australian businesses currently conduct to obtain customer insights. However, these reviews are unstructured and require substantial pre-processing to extract underlying customer perceptions. Therefore, this project aims to ....Harnessing Business Insights from Unstructured Customer Data. Resulting from customers’ widespread uptake of online channels to buy and communicate has been a surge in online reviews and social media posts. This textual information offers a viable alternative to surveys that Australian businesses currently conduct to obtain customer insights. However, these reviews are unstructured and require substantial pre-processing to extract underlying customer perceptions. Therefore, this project aims to develop a novel machine learning approach to quantify the business-relevant information contained in textual information shared by customers online. This alternative approach will provide significant cost-saving benefits for a range of Australian companies, such as retailers, hotels, airlines and restaurants.Read moreRead less
Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into so ....Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals. Read moreRead less
Innovative Use of Customer Data for Business Growth. This project aims to apply and adapt the latest machine learning techniques to enable companies to utilise their existing customer data to reveal purchase motivations, product preferences, and responsiveness to marketing communications for each single customer. A widespread practice in marketing is to partition customers into broad groups, but customers expect products and services that are tailored to their individual needs. This presents ex ....Innovative Use of Customer Data for Business Growth. This project aims to apply and adapt the latest machine learning techniques to enable companies to utilise their existing customer data to reveal purchase motivations, product preferences, and responsiveness to marketing communications for each single customer. A widespread practice in marketing is to partition customers into broad groups, but customers expect products and services that are tailored to their individual needs. This presents extreme challenges due to the size and complexity of customer databases. The expected outcomes will enable Australian companies to attract and retain more customers, and make more efficient use of their marketing budget. Benefits include equipping companies to better compete domestically and globally.Read moreRead less