Linkage Infrastructure, Equipment And Facilities - Grant ID: LE240100131
Funder
Australian Research Council
Funding Amount
$539,000.00
Summary
Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boo ....Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boost Australia’s pivotal research leadership and business competitiveness in nurturing new-generation, collaborative and transformative digital R&D and talent pipeline. It will enable large-scale strategic business innovation and transformation including smart manufacturing and Industry 4.0.Read moreRead less
Towards Generalisable and Unbiased Dynamic Recommender Systems. This project aims to develop the foundations, including models, methodology, and algorithms for building generalisable and unbiased dynamic recommender systems to facilitate intelligent decision-making, prompt contextualised and personalised strategic plans, and support context-aware action recourse. To ensure that fundamental principles, such as fairness and transparency, are respected, a set of algorithms and techniques are propos ....Towards Generalisable and Unbiased Dynamic Recommender Systems. This project aims to develop the foundations, including models, methodology, and algorithms for building generalisable and unbiased dynamic recommender systems to facilitate intelligent decision-making, prompt contextualised and personalised strategic plans, and support context-aware action recourse. To ensure that fundamental principles, such as fairness and transparency, are respected, a set of algorithms and techniques are proposed to develop recommender systems in a more responsible manner. The result of this project will not only maintain Australia's leadership in this frontier research area, but also serve as an excellent vehicle for the education and training of Australia's next generation of scholars and engineers.Read moreRead less
Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, ....Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, statistics and different ways of aggregating information. By building a more complete theoretical map it is expected that new machine learning methods will be developed, but more importantly that machine learning will be able to be better integrated into larger socio-technical systems.Read moreRead less
Understanding Dynamic Aspects of Economic Inequality. This project aims to study dynamic aspects of inequality in Australia by exploring the changes in labour and housing market conditions and their relation to the changes in the distribution of income and wealth over the last decade. The project also aims to develop new econometric techniques to examine the factors that are responsible for the changes in the distribution of income and wealth and a range of labour and housing market outcomes. Pa ....Understanding Dynamic Aspects of Economic Inequality. This project aims to study dynamic aspects of inequality in Australia by exploring the changes in labour and housing market conditions and their relation to the changes in the distribution of income and wealth over the last decade. The project also aims to develop new econometric techniques to examine the factors that are responsible for the changes in the distribution of income and wealth and a range of labour and housing market outcomes. Particular attention will be paid to the role of the changes in individual-specific characteristics (such as education, age, employment status, and occupation) and neighbourhood-specific characteristics (such as house prices and population ageing) in producing inequality.Read moreRead less
Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algori ....Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algorithms for applied researchers. This project benefits not only advanced manufacturing by finding optimal stopping time for wood panel compression, but also superior forecasting for mortality in demography, climate data in environmental science, asset returns in finance, and electricity consumption in economics. Read moreRead less
Profiling And Tracking Change In Australia's Seafood Workforce: Establishing A Baseline Workforce Dataset
Funder
Fisheries Research and Development Corporation
Funding Amount
$259,342.00
Summary
The project developed to address the call for EOI recognises that the seafood workforce is diverse and operates within a changing natural, technological, and socioeconomic environment, providing unique challenges and opportunities. The seafood workforce also, however, operates within the wider Australian economy where rural and regional employment, small-medium business operations, and increasing value-adding opportunities are common topics of interest. The project proposes to provide a comprehe ....The project developed to address the call for EOI recognises that the seafood workforce is diverse and operates within a changing natural, technological, and socioeconomic environment, providing unique challenges and opportunities. The seafood workforce also, however, operates within the wider Australian economy where rural and regional employment, small-medium business operations, and increasing value-adding opportunities are common topics of interest. The project proposes to provide a comprehensive assessment of the current data framework, make recommendations for improving it, and develop a baseline workforce dataset. The focus will be on the potential to use existing sources of data (particularly administrative data collected by government institutions and data that is required to be collected) and how and when those need to be effectively complemented with additional data. Administrative data are confidential and access limited as is the variety of seafood industry data often collected. Accessing administrative data is explicitly part of this proposal and identifying the sources of, and the type of data available, from industry surveys. Objectives: 1. To establish a baseline workforce dataset to address the lack of accessible, accurate workforce data 2. To identify how to overcome the shortcomings of official classifications to better align data information with how the seafood industry and its workforce operate. 3. To determine how using whole of population statistical data may provide a more accurate picture of the seafood industry workforce 4. To use available literature and expert input to provide an understanding of the true diversity of employment in the seafood sector. 5. To undertake a comprehensive stock-take of the relevant current data sources recording information on the seafood industry workforce. 6. To undertake a comprehensive analysis of the existing data sources and investigate the usefulness of large administrative data such as BLADE/MADIP. 7. To closely involve seafood industry participants through an effective stakeholder engagement strategy and promote a co-design element to the project 8. To provide recommendations to address data gaps and improve the utility of current data, and support the FRDC in meeting the objectives of its Capability and Capacity Building Strategy. Read moreRead less
Rigorous Privacy Compliance in Modern Application Ecosystems. Modern network applications such as mobile applications and browser extensions have become the primary gateways for consumers to access the Internet in today’s digital landscape. This project aims to address privacy issues in these ecosystems by developing a new privacy-compliance assessment framework. The framework will evaluate the current privacy practices of application ecosystems, enabling users and developers in Australia and wo ....Rigorous Privacy Compliance in Modern Application Ecosystems. Modern network applications such as mobile applications and browser extensions have become the primary gateways for consumers to access the Internet in today’s digital landscape. This project aims to address privacy issues in these ecosystems by developing a new privacy-compliance assessment framework. The framework will evaluate the current privacy practices of application ecosystems, enabling users and developers in Australia and worldwide to reliably identify potential privacy risks and issues on their applications. The intended outcomes should endow data controllers with the capability of evidencing their compliance of data protection legislations such as Australia Privacy Act 1988 and EU General Data Protection Regulation (GDPR).Read moreRead less
Theoretical Foundations of Ethical Machine Learning. The project aims to develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project aims to develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification ....Theoretical Foundations of Ethical Machine Learning. The project aims to develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project aims to develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification of the inevitable trade-offs between fairness and utility. The benefits of the project should include better ways of managing these trade-offs, a competitive advantage for Australian firms developing the technology, and will ensure that the country retains a social license to use the technology.Read moreRead less
Regional Comparisons of Prices, Income and Growth in Australia. We will measure how much the cost of living and rates of inflation differ across the eight capital cities in Australia, and then test whether real per capita income levels across cities are converging or diverging over time. To make such comparisons, the ABS's databases on each capital city must first be harmonized. While doing this we will review the ABS's current procedures for data construction and quality assessment. A further a ....Regional Comparisons of Prices, Income and Growth in Australia. We will measure how much the cost of living and rates of inflation differ across the eight capital cities in Australia, and then test whether real per capita income levels across cities are converging or diverging over time. To make such comparisons, the ABS's databases on each capital city must first be harmonized. While doing this we will review the ABS's current procedures for data construction and quality assessment. A further aim is to show how statistical modelling using spanning-tree methods can resolve the conflict that arises for price indexes constructed on panel data sets between temporal and spatial consistency.Read moreRead less
Socio-Economic Study Of The Eastern Gemfish Fishery
Funder
Fisheries Research and Development Corporation
Funding Amount
$36,000.00
Summary
Objectives: 1. Identify and develop practical closure options for the eastern gemfish fishery. 2. Assess each option in terms of: a. the estimated reduction in the kill of eastern gemfish and the benefits there of to the future recovery of the stock; and b the estimated net value of catch directly forgone of other SEF quota species. c key non-quota species. 3. Based on the above assessment determine, as compared to current management arrangements, the direct socio-economic net ....Objectives: 1. Identify and develop practical closure options for the eastern gemfish fishery. 2. Assess each option in terms of: a. the estimated reduction in the kill of eastern gemfish and the benefits there of to the future recovery of the stock; and b the estimated net value of catch directly forgone of other SEF quota species. c key non-quota species. 3. Based on the above assessment determine, as compared to current management arrangements, the direct socio-economic net benefits or costs to groups of fishing operators based in key southern NSW and eastern Victorian ports and to SEF operators as a whole. 4. Determine a preferred closure option and evaluate the overall effectiveness of this option against current management options, taking into account: a. the quantity of gemfish that may be killed. b. the direct and indirect socio-economic effects. c. management costs. d. the perceived support from the fishing. industry and other groups - the objectives of the Fisheries Management Act 1991. 5. Prepare a draft report by 14 September 1995 and a final report by 30 September 1995. Read moreRead less