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Scheme : Linkage Projects
Research Topic : Image processing
Australian State/Territory : TAS
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  • Funded Activity

    Linkage Projects - Grant ID: LP0882176

    Funder
    Australian Research Council
    Funding Amount
    $220,000.00
    Summary
    Supporting personalised learning in secondary schools through the use of specific mathematics assessments that reveal thinking. This project will improve numeracy standards in secondary schools, by assisting teachers to personalise the teaching of each student. Through detailed research, the project will develop sophisticated assessments that clearly reveal students' mathematical thinking. On-line diagnosis will suggest teaching activities that can bring about desired conceptual changes. The eff .... Supporting personalised learning in secondary schools through the use of specific mathematics assessments that reveal thinking. This project will improve numeracy standards in secondary schools, by assisting teachers to personalise the teaching of each student. Through detailed research, the project will develop sophisticated assessments that clearly reveal students' mathematical thinking. On-line diagnosis will suggest teaching activities that can bring about desired conceptual changes. The effectiveness of the resources will be thoroughly tested, for impact on student achievement and the mathematics teaching skills of teachers, especially those working out-of-field. Rural schools will have equal access to these resources. Good numeracy provides the foundation for life-long learning, employment satisfaction and the economic competitiveness of Australia.
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    Funded Activity

    Linkage Projects - Grant ID: LP150101090

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    Improving Signal Detection Range of Active Seismic Monitoring in Mines. This project will develop a new generation of sensors that will process incoming seismic waves from an active source to accurately estimate the properties of underground rock mass in real time. This will lead to safer mining operations that will decrease the number of injuries and deaths. A probability graph model will be used to fuse measurements from different sensors to produce more accurate estimates of the rock mass. A .... Improving Signal Detection Range of Active Seismic Monitoring in Mines. This project will develop a new generation of sensors that will process incoming seismic waves from an active source to accurately estimate the properties of underground rock mass in real time. This will lead to safer mining operations that will decrease the number of injuries and deaths. A probability graph model will be used to fuse measurements from different sensors to produce more accurate estimates of the rock mass. A new low-cost seismic source will excite large areas of rock mass for continuous monitoring of the changes in stress and fracture density caused by mining. This will lead to methodologies that will significantly improve mining operations and increase Australia’s productivity in the mining sector.
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    Funded Activity

    Linkage Projects - Grant ID: LP160100935

    Funder
    Australian Research Council
    Funding Amount
    $382,000.00
    Summary
    Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar .... Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.
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