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Research Topic : statistics
Australian State/Territory : TAS
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  • Funded Activity

    Discovery Projects - Grant ID: DP110101663

    Funder
    Australian Research Council
    Funding Amount
    $600,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0877447

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Markov invariants and phylogenetic tree reconstruction. The project will assist Australia to progress as an innovator in the production phylogenetic tree reconstruction techniques. Identifying species is a difficult task with environmental, social and economic benefits to Australia. DNA evidence and phylogenetic methods clearly achieve this task. Conservation of rare species depends upon identification and hence robust phylogenetic analysis. Phylogenetically identifying fish species has econom .... Markov invariants and phylogenetic tree reconstruction. The project will assist Australia to progress as an innovator in the production phylogenetic tree reconstruction techniques. Identifying species is a difficult task with environmental, social and economic benefits to Australia. DNA evidence and phylogenetic methods clearly achieve this task. Conservation of rare species depends upon identification and hence robust phylogenetic analysis. Phylogenetically identifying fish species has economic importance as different fish species are all managed separately, having different catch limits, catch areas and market values. Using effective phylogenetic methods, epidemiologists can track the spread of a disease through a population.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP170100555

    Funder
    Australian Research Council
    Funding Amount
    $460,000.00
    Summary
    Remote sensing to improve structural efficiency of high-speed catamarans. This project aims to develop a monitoring system to remotely measure ship motions, loads and ride control activity under commercial operations. Data will be analysed using advanced statistical methods to inform evidence-based design to improve both structural efficiency and passenger comfort. The research will impact on design rules used worldwide, reducing weight and increasing payload and transport efficiency for this cl .... Remote sensing to improve structural efficiency of high-speed catamarans. This project aims to develop a monitoring system to remotely measure ship motions, loads and ride control activity under commercial operations. Data will be analysed using advanced statistical methods to inform evidence-based design to improve both structural efficiency and passenger comfort. The research will impact on design rules used worldwide, reducing weight and increasing payload and transport efficiency for this class of vessel. A "Smart” semi-autonomous interface will be developed to provide on-board seakeeping guidance to the ship captain. This technology will have significant benefits such as increased ship safety, vessel longevity and improving passenger comfort for all types of vessels worldwide including high-speed catamarans.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP180100352

    Funder
    Australian Research Council
    Funding Amount
    $317,329.00
    Summary
    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.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100152

    Funder
    Australian Research Council
    Funding Amount
    $410,000.00
    Summary
    Modeling Healthcare Systems. An efficient healthcare system is essential for the well-being of any society. The aim of the project is to develop major advances in the mathematical modelling of healthcare systems, in order to improve efficiency, and ultimately, patient health. The first expected outcome is the development of mathematical models that constitute a high-level description of patient flow through hospitals and subacute care, so that demands for emergency and elective capacity are met .... Modeling Healthcare Systems. An efficient healthcare system is essential for the well-being of any society. The aim of the project is to develop major advances in the mathematical modelling of healthcare systems, in order to improve efficiency, and ultimately, patient health. The first expected outcome is the development of mathematical models that constitute a high-level description of patient flow through hospitals and subacute care, so that demands for emergency and elective capacity are met given limited resources. The second is the development of a bed allocation algorithm that allocates patients to appropriate wards, so as to optimise the set of performance indicators of the system under appropriate constraints, given the current ward occupancy.
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