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Australian State/Territory : QLD
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Research Topic : Applied Computing
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  • Funded Activity

    Discovery Projects - Grant ID: DP0342985

    Funder
    Australian Research Council
    Funding Amount
    $135,000.00
    Summary
    New Developments for Bayesian statistical models and computational methods. Bayesian methods of statistical analysis provide a flexible theory for addressing inference in the presence of uncertainty. Consequently Bayesian methods have enabled scientific discovery in areas characterised as complex systems where new developments in modelling and computational methods have been crucial. Significant barriers to further success involve challenges in formulating and validating models, dealing with l .... New Developments for Bayesian statistical models and computational methods. Bayesian methods of statistical analysis provide a flexible theory for addressing inference in the presence of uncertainty. Consequently Bayesian methods have enabled scientific discovery in areas characterised as complex systems where new developments in modelling and computational methods have been crucial. Significant barriers to further success involve challenges in formulating and validating models, dealing with large data sets, and developing efficient computational methods. The principal aim of this project is to develop new Bayesian modelling and computational methodology which address these challenges with broad application.
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    Funded Activity

    Linkage Projects - Grant ID: LP0214188

    Funder
    Australian Research Council
    Funding Amount
    $110,135.00
    Summary
    A toolkit of statistical methodology for a state-of-the-art software and decision support system for forest assessment using new airborne data. The aim is to develop statistical methods for efficient collection and interpretation of airborne laser data and videography, used to describe characteristics of the forest such as tree species, stand history and vertical distribution of foliage, and hence biodiversity and biomass. This is significant for meeting Australia's international and national en .... A toolkit of statistical methodology for a state-of-the-art software and decision support system for forest assessment using new airborne data. The aim is to develop statistical methods for efficient collection and interpretation of airborne laser data and videography, used to describe characteristics of the forest such as tree species, stand history and vertical distribution of foliage, and hence biodiversity and biomass. This is significant for meeting Australia's international and national environmental obligations, providing quality information to farmers and industry, and hence developing potential jobs in regional areas. Outcomes include a toolkit of statistical methods applicable to spatial modelling and analysis of very large datasets, a statistically valid software product, marketable estimation methods in carbon accounting, technology transfer, training, publications.
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    Funded Activity

    Discovery Projects - Grant ID: DP0877624

    Funder
    Australian Research Council
    Funding Amount
    $435,000.00
    Summary
    Novel Applied Bayesian Statistics for Monitoring Neuromuscular Diseases. Neurological diseases such as motor neurone disease are caused by the progressive death of motor units serving a muscle. Currently there are no ways of quantifying and detecting change in the number of motor units serving a muscle which are non-invasive. Our research will provide an objective method for the progression of neuromuscular diseases to be monitored with minimal inconvenience to patients. This will allow clinic .... Novel Applied Bayesian Statistics for Monitoring Neuromuscular Diseases. Neurological diseases such as motor neurone disease are caused by the progressive death of motor units serving a muscle. Currently there are no ways of quantifying and detecting change in the number of motor units serving a muscle which are non-invasive. Our research will provide an objective method for the progression of neuromuscular diseases to be monitored with minimal inconvenience to patients. This will allow clinical trials for possible effective treatments of neurological diseases such as motor neurone disease to be conducted with an objective measurement of disease progression.
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    Funded Activity

    ARC Centres Of Excellence - Grant ID: CE0348165

    Funder
    Australian Research Council
    Funding Amount
    $13,749,290.00
    Summary
    ARC Centre for Complex Dynamic Systems & Control. Complex dynamic systems are an inescapable feature of the world we live in. Modelling, analysing and optimizing complex behaviour is crucial for environment, process industry, biomedical, energy distribution, transportation and other applications. The Centre for Complex Dynamic Systems and Control will become an international authority in the analysis, design and optimization of complex dynamic systems, pursuing both outstanding fundamental and c .... ARC Centre for Complex Dynamic Systems & Control. Complex dynamic systems are an inescapable feature of the world we live in. Modelling, analysing and optimizing complex behaviour is crucial for environment, process industry, biomedical, energy distribution, transportation and other applications. The Centre for Complex Dynamic Systems and Control will become an international authority in the analysis, design and optimization of complex dynamic systems, pursuing both outstanding fundamental and cutting edge applied research outcomes. These outcomes will be of specific benefit to partner organizations including minerals, process, metal forming, and automotive industries.
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    Funded Activity

    Discovery Projects - Grant ID: DP0772887

    Funder
    Australian Research Council
    Funding Amount
    $895,099.00
    Summary
    Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most .... Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most industries in Australia. More specifically, it is to be applied here to the diagnosis and prognosis of ovarian cancer. This cross-disciplinary project will strengthen Australian researchers' capacity and capability of participating in cutting-edge DNA microarray research.
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    Funded Activity

    Linkage Projects - Grant ID: LP0560544

    Funder
    Australian Research Council
    Funding Amount
    $160,000.00
    Summary
    Elicitation and Integration of Expert Information for Natural Resource Management with a Focus on Water. Australia's natural resource management requires integrating information from many sources, including survey data and community and expert opinion. We aim to develop statistical methods to formally combine this information and apply them to better management of our crucial resource, water. The project contributes significantly to Australia's international obligations, and government agency an .... Elicitation and Integration of Expert Information for Natural Resource Management with a Focus on Water. Australia's natural resource management requires integrating information from many sources, including survey data and community and expert opinion. We aim to develop statistical methods to formally combine this information and apply them to better management of our crucial resource, water. The project contributes significantly to Australia's international obligations, and government agency and regional group science-based decision-making. Outcomes include increased fundamental knowledge in statistics, technology transfer and improved decision-making capacity for natural resource management. The project builds on strong existing collaborations between academic and industry partners and provides foundation for future funded projects.
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    Funded Activity

    Linkage Projects - Grant ID: LP0668185

    Funder
    Australian Research Council
    Funding Amount
    $381,000.00
    Summary
    Measuring and presenting uncertainty in complex natural resource monitoring programs. This project addresses Australia's key research goal of An Environmentally Sustainable Australia, priority goals of Water, Soil and Climate, and the theme of Complex Systems.Through improved capability in making data-based decisions and true sharing of university and government agency expertise, the project will enhance Australia's ability to better manage its natural resources, meet national and international .... Measuring and presenting uncertainty in complex natural resource monitoring programs. This project addresses Australia's key research goal of An Environmentally Sustainable Australia, priority goals of Water, Soil and Climate, and the theme of Complex Systems.Through improved capability in making data-based decisions and true sharing of university and government agency expertise, the project will enhance Australia's ability to better manage its natural resources, meet national and international environmental commitments, and address national demands for quality science underpinning decisions about natural resource management
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    Funded Activity

    Discovery Projects - Grant ID: DP0345901

    Funder
    Australian Research Council
    Funding Amount
    $165,000.00
    Summary
    Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discove .... Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.
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