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  • Researchers (20)
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  • Funded Activity

    Discovery Projects - Grant ID: DP0343727

    Funder
    Australian Research Council
    Funding Amount
    $385,000.00
    Summary
    Statistical Advances in the Post-Genome Era. Biologically relevant statistical foundations for post-genome biology and biotechnology will be developed. Specific goals of the topics include the development of accurate and more efficient algorithms for sequence alignments, improved models to maximise the accuracy of analyses for gene expression data and superior statistical methods for identification of complex gene networks that predispose an organism to disease. The Project will make significant .... Statistical Advances in the Post-Genome Era. Biologically relevant statistical foundations for post-genome biology and biotechnology will be developed. Specific goals of the topics include the development of accurate and more efficient algorithms for sequence alignments, improved models to maximise the accuracy of analyses for gene expression data and superior statistical methods for identification of complex gene networks that predispose an organism to disease. The Project will make significant contributions to the new and evolving priority research area of Bioinformation Science (including bioinformatics). Outcomes will include novel techniques for analysis and mining of post-genome data, with applications to developments in Bio-medicine and Bio-agriculture
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    Funded Activity

    Linkage Projects - Grant ID: LP0562008

    Funder
    Australian Research Council
    Funding Amount
    $446,599.00
    Summary
    Investment Approaches and Applications in Financial Markets: Evolutionary Kernel Based Subset Time-Series Using Semi-Parametric Approaches. The project will develop new investment assessments based on subset time-series modeling. Innovative evolutionary kernel smoothing algorithms using semi-parametric approaches will be introduced. The project will make three important applications of this modeling in financial markets: a) benchmarking and evaluation of inflation-indexed bonds; b) evaluation of .... Investment Approaches and Applications in Financial Markets: Evolutionary Kernel Based Subset Time-Series Using Semi-Parametric Approaches. The project will develop new investment assessments based on subset time-series modeling. Innovative evolutionary kernel smoothing algorithms using semi-parametric approaches will be introduced. The project will make three important applications of this modeling in financial markets: a) benchmarking and evaluation of inflation-indexed bonds; b) evaluation of the performance of global diversified investment funds; and c) prediction to provide early warning of the emergence of destabilising deflation or inflation. These three applications will lead to improved risk management practices and investment performance. Recursive algorithms will provide new statistical methods to study investment asset price movements and market volatility.
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    Funded Activity

    Discovery Projects - Grant ID: DP1092801

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of .... The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of complexity arising in climate change involve issues on which we do not possess a deep understanding. This project draws upon a set of inter-disciplinary concepts and models centred in neural networks that enable us to advance our understanding of complexity, leading to superior quantitative tools and models to allow for improved environmental decision-making.
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    Funded Activity

    Linkage Projects - Grant ID: LP0989811

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Investment approaches and opportunities in renewable energy and financial resource markets, using semi-parametric approaches to evolutionary subset time-series lattice-ladder modelling. The project findings will help Australian exporters and importers understand and manage energy and resource price risks more effectively. The investment community will benefit through selecting optimal asset allocations and enhancing value to investors. It will also benefit many other agencies, particularly in th .... Investment approaches and opportunities in renewable energy and financial resource markets, using semi-parametric approaches to evolutionary subset time-series lattice-ladder modelling. The project findings will help Australian exporters and importers understand and manage energy and resource price risks more effectively. The investment community will benefit through selecting optimal asset allocations and enhancing value to investors. It will also benefit many other agencies, particularly in the service industries. It is not well recognised that in developed countries, including Australia, the financial service and related sectors account for more than 60 percent of economic activity and employment, so it is critical that more sophisticated statistical methods be established, and practical applications conducted, in order to advance the understanding of complexity management in the financial service and related sectors.
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    Funded Activity

    Linkage Projects - Grant ID: LP0883801

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    The improvement of investment approaches by developing and applying bootstrap methods to innovative evolutionary kernel-based subset time-series modelling. With over $1 trillion of investors' monies in the hands of fund managers, the importance of efficient investment decisions across all industry sectors is self evident. Even if the modest target of systematically improving decision making by 1 or 2 % is set, the aggregate economic benefit achieved, given the compounding effects will be enormou .... The improvement of investment approaches by developing and applying bootstrap methods to innovative evolutionary kernel-based subset time-series modelling. With over $1 trillion of investors' monies in the hands of fund managers, the importance of efficient investment decisions across all industry sectors is self evident. Even if the modest target of systematically improving decision making by 1 or 2 % is set, the aggregate economic benefit achieved, given the compounding effects will be enormous. Any developed or developing country will profit from such advanced decision-making approaches. Therefore it is critical that more sophisticated statistical methods be established, and practical applications conducted, in order to advance the understanding of complexity management in the financial investment and other relevant sectors.
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    Funded Activity

    Discovery Projects - Grant ID: DP1094699

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    Mathematical Methods for Next Generation Sequencing. The emergence of a new generation of high throughput genomic sequencing technologies is providing unprecedented opportunities for biological research. Hidden within the huge amounts of data generated by this technology is information about the expression and regulation of genes, and the complex functional purpose of non-coding, so called 'junk', DNA. Development of mathematical and statistical tools is essential to interpreting these data. The .... Mathematical Methods for Next Generation Sequencing. The emergence of a new generation of high throughput genomic sequencing technologies is providing unprecedented opportunities for biological research. Hidden within the huge amounts of data generated by this technology is information about the expression and regulation of genes, and the complex functional purpose of non-coding, so called 'junk', DNA. Development of mathematical and statistical tools is essential to interpreting these data. The proposed research will enhance Australia's reputation for developing novel quantitative techniques at the cutting edge of modern biology. The proposed project has a broad range of potential applications in biotechnology, particularly in the medical and agricultural industries.
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    Funded Activity

    Discovery Projects - Grant ID: DP1096243

    Funder
    Australian Research Council
    Funding Amount
    $195,000.00
    Summary
    Risk Measures and Management in Finance and Actuarial Science Under Regime-Switching Models. New models for assessing and managing risk of financial products will place Australia at the forefront of risk management. The work will also sustain the competitive edge of Australia as one of the major financial centres in the Asia-Pacific region through enhancing both the theory and practice of financial risk management. The project outcome will also benefit to the country in other areas of risk, for .... Risk Measures and Management in Finance and Actuarial Science Under Regime-Switching Models. New models for assessing and managing risk of financial products will place Australia at the forefront of risk management. The work will also sustain the competitive edge of Australia as one of the major financial centres in the Asia-Pacific region through enhancing both the theory and practice of financial risk management. The project outcome will also benefit to the country in other areas of risk, for example, environment risk, climate change, and energy and security problems.
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    Funded Activity

    Linkage Projects - Grant ID: LP0669259

    Funder
    Australian Research Council
    Funding Amount
    $73,950.00
    Summary
    Precise Atmospheric Density Correction Model Using Space Tracking Data for Accurate Debris Surveillance and Collision Warning. Our project will build new atmospheric density correction models (ADCMs) for accurate prediction of debris object and satellite orbits. This research will have tremendous impacts on realizing unaided debris laser ranging. An order of magnitude accuracy improvement to the ADCMs will lead to a significant breakthrough in space object tracking. The benefits of this research .... Precise Atmospheric Density Correction Model Using Space Tracking Data for Accurate Debris Surveillance and Collision Warning. Our project will build new atmospheric density correction models (ADCMs) for accurate prediction of debris object and satellite orbits. This research will have tremendous impacts on realizing unaided debris laser ranging. An order of magnitude accuracy improvement to the ADCMs will lead to a significant breakthrough in space object tracking. The benefits of this research are: it will put Australia in a leading position in the world on ADCM study; to maintain Australia's leading role in space surveillance and greatly enhanced operational capability & efficiency of Australian space tracking systems; and to contribute significantly to the space environment info management, e.g. accurate collision warning and space junk tracking.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT0991594

    Funder
    Australian Research Council
    Funding Amount
    $683,400.00
    Summary
    Increasing internet energy and cost efficiency by improving higher-layer protocols. Australians rely heavily on our telecommunications infrastructure due to our geographic dispersion. We are also very susceptible to climate change, given our reliance on agriculture. Information technology is consuming a rapidly increasing fraction of our power and our budget. This research will help to reverse both those trends, by finding novel and practical ways to use our infrastructure more efficiently, and .... Increasing internet energy and cost efficiency by improving higher-layer protocols. Australians rely heavily on our telecommunications infrastructure due to our geographic dispersion. We are also very susceptible to climate change, given our reliance on agriculture. Information technology is consuming a rapidly increasing fraction of our power and our budget. This research will help to reverse both those trends, by finding novel and practical ways to use our infrastructure more efficiently, and to minimise its energy use. This will enable the Australian telecommunications industry to provide better service (including to Australian industries and rural communities) at lower economic and environmental cost. This project will put Australia on the international stage as a leading contributor to energy-efficient internet technology.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT0992081

    Funder
    Australian Research Council
    Funding Amount
    $624,300.00
    Summary
    Fatigue Life Prediction of Nano-filler Modified Composites. The proposed project aims to study the behaviour and the failure mechanisms of polymer nanocomposites under cyclic loading. The outcomes of the project will make original contributions to our knowledge base on such materials. The mechanics modelling and statistical analysis of the prediction of fatigue life will provide a sound physical basis and a useful tool for any future improvement and optimisation of the composites to achieve bett .... Fatigue Life Prediction of Nano-filler Modified Composites. The proposed project aims to study the behaviour and the failure mechanisms of polymer nanocomposites under cyclic loading. The outcomes of the project will make original contributions to our knowledge base on such materials. The mechanics modelling and statistical analysis of the prediction of fatigue life will provide a sound physical basis and a useful tool for any future improvement and optimisation of the composites to achieve better reliability and integrity in their intended applications. This study will bring economic benefits to the end-users of advanced material technology including the Australian materials industries.
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