Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact netw ....Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact networks to develop robust predictions of disease spread and population fate, and to reliably predict the outcomes of management interventions. These robust prediction methods will provide better insights for conservation of Australian wildlife.Read moreRead less
Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire ....Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire risk and spread, trained and validated on a two-decade satellite fire record. The predictive ability of the model will be tested on the 2019/20 fire season to determine if novel drivers of fire can be identified, and the model itself will be operationalised into a novel short-to-mid term fire risk prediction tool. Read moreRead less
Advanced matrix-analytic methods with applications. Over the last twenty-five years, matrix-analytic methods have proved to be very successful in formulating and analysing certain classes of stochastic models. Motivated by applications, this project will investigate more advanced matrix-analytic methods than have hitherto been studied.
Managing Fresh-Water Resources in Saline Environments. Australian industry and urban developments often rely on a secure supply of fresh water. In many situations, the fresh water occurs adjacent to large expanses of saline water. This poses special constraints on how the fresh water can be recovered. This project undertakes careful mathematical modelling of fresh water recovery from reservoirs and from within islands (where it may be the only practical source of drinking water). The injecti ....Managing Fresh-Water Resources in Saline Environments. Australian industry and urban developments often rely on a secure supply of fresh water. In many situations, the fresh water occurs adjacent to large expanses of saline water. This poses special constraints on how the fresh water can be recovered. This project undertakes careful mathematical modelling of fresh water recovery from reservoirs and from within islands (where it may be the only practical source of drinking water). The injection and extraction of ground water in novel "mineral leaching" mining technology will also be investigated.Read moreRead less
Creating new stochastic models to understand the evolution of gene families. This project aims to extend stochastic modelling techniques in order to develop mathematically rigorous and biologically relevant models for the evolution of gene families. The project expects to model evolutionary processes such as gene retention, duplication and loss, and the generation of new gene functions. The duplication and subsequent re-purposing of genes is thought to be a key mechanism for generating evolution ....Creating new stochastic models to understand the evolution of gene families. This project aims to extend stochastic modelling techniques in order to develop mathematically rigorous and biologically relevant models for the evolution of gene families. The project expects to model evolutionary processes such as gene retention, duplication and loss, and the generation of new gene functions. The duplication and subsequent re-purposing of genes is thought to be a key mechanism for generating evolutionary novelty. By applying these models to genome data, the project expects to be able to quantify the importance of these different evolutionary mechanisms. The project will strengthen collaborative links between researchers in stochastic modelling and molecular evolutionary biology.Read moreRead less
Prediction of radiated noise from marine propellers. Underwater noise radiated from marine vessels is a significant problem for research, fishing and military vessels, and is a major source of pollution in the marine environment. The major source contributing to underwater noise is due to the propeller. This work will develop numerical models with experimental validation that can accurately predict the sources of noise generated by marine propellers and acoustic signatures of marine vessels due ....Prediction of radiated noise from marine propellers. Underwater noise radiated from marine vessels is a significant problem for research, fishing and military vessels, and is a major source of pollution in the marine environment. The major source contributing to underwater noise is due to the propeller. This work will develop numerical models with experimental validation that can accurately predict the sources of noise generated by marine propellers and acoustic signatures of marine vessels due to propeller motion. This work has great significance for Australia’s construction and military maritime industries. The technologies developed in this project are also applicable to rotors in other industries such as in aircraft, helicopters and wind turbines.Read moreRead less
An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will r ....An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will rectify this situation by using representation theory to transform combinatorial group theory into linear algebra, allowing for the application of advanced methods of numeric approximation. This will provide a better understanding of how bacteria evolve and improve our ability to manage their impact.Read moreRead less
Powerful knowledge: mapping out standards of teachers' knowledge for teaching mathematics and English to achieve the goals of the curriculum. Setting standards is an important step to raising teacher quality. This project will establish benchmarks for teachers' knowledge at all levels of schooling in two key areas of the curriculum: English and mathematics.
Modelling with data: Advancing STEM in the primary curriculum. Improving the nation's skills in Science, Technology, Engineering, and Mathematics (STEM) remains a continuing concern, especially given the decline in international test results. The project aims to introduce a new approach to promoting this learning across grades 3-6 through modelling with data. With a focus on inquiry processes involving data variation and uncertainty within STEM-based contexts, the project aims to develop the imp ....Modelling with data: Advancing STEM in the primary curriculum. Improving the nation's skills in Science, Technology, Engineering, and Mathematics (STEM) remains a continuing concern, especially given the decline in international test results. The project aims to introduce a new approach to promoting this learning across grades 3-6 through modelling with data. With a focus on inquiry processes involving data variation and uncertainty within STEM-based contexts, the project aims to develop the important mathematical and statistical literacies needed for lifting student achievements. In advancing both theory and practice, the project aims to contribute to knowledge of primary students' capabilities for STEM problem solving and ways of enhancing implementation of the Australian Curriculum.Read moreRead less
Talking Maths: Bridging the gap through talk in Early Years mathematics . The study aims to address the gap in mathematical performance in Australia in relation to socioeconomic status (SES) by focusing on language and learning in mathematics. The study will design and evaluate a school-based intervention that positions language through talk as a key resource in teaching mathematics in Grades 1 and 2. Outcomes of the study will be empirical evidence of the effect of a language-based pedagogy on ....Talking Maths: Bridging the gap through talk in Early Years mathematics . The study aims to address the gap in mathematical performance in Australia in relation to socioeconomic status (SES) by focusing on language and learning in mathematics. The study will design and evaluate a school-based intervention that positions language through talk as a key resource in teaching mathematics in Grades 1 and 2. Outcomes of the study will be empirical evidence of the effect of a language-based pedagogy on young students' achievement in mathematics and further understanding of the relationship between talk and learning. These outcomes will inform policy and teacher education and have a long lasting impact on low SES students' educational and work opportunities with ultimate impact on economic and cultural prosperity.
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