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Research Topic : Diagnositc algorithms
Field of Research : Computer Software
Australian State/Territory : NSW
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  • Funded Activity

    Discovery Projects - Grant ID: DP0560190

    Funder
    Australian Research Council
    Funding Amount
    $150,000.00
    Summary
    Compilation Techniques for Embedded Systems. Highly optimising compiler tools are becoming an important part of the software development process for embedded systems. This project will provide Australia with core technology in the area of tools for embedded systems. It will allow safer embedded systems in mission-critical applications. In addition, the Australian Industry will benefit from a substantially growing embedded systems market where tools are a pre-requisite for a cost-aware and safe s .... Compilation Techniques for Embedded Systems. Highly optimising compiler tools are becoming an important part of the software development process for embedded systems. This project will provide Australia with core technology in the area of tools for embedded systems. It will allow safer embedded systems in mission-critical applications. In addition, the Australian Industry will benefit from a substantially growing embedded systems market where tools are a pre-requisite for a cost-aware and safe software development. The industry interested in embedded system tools are: Telecom/Datacom, Consumer Electronics, Industrial Automation, Retail Automation, Office Automation, Military/Aerospace, Automotive, Information Automation, Medical Devices.
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    Funded Activity

    Discovery Projects - Grant ID: DP0985271

    Funder
    Australian Research Council
    Funding Amount
    $230,000.00
    Summary
    An Integrative and Interactive Approach for Co-estimation of Multiple Sequence Alignment and Phylogeny Reconstruction. In this project innovative IT methods will be developed to assist biologists to solve complex and important biological problems. Many important applications in computational biology need very accurate and reliable tools for multiple sequence alignment and phylogeny reconstruction. Unfortunately, current existing tools are unreliable and are prone to serious errors when applied t .... An Integrative and Interactive Approach for Co-estimation of Multiple Sequence Alignment and Phylogeny Reconstruction. In this project innovative IT methods will be developed to assist biologists to solve complex and important biological problems. Many important applications in computational biology need very accurate and reliable tools for multiple sequence alignment and phylogeny reconstruction. Unfortunately, current existing tools are unreliable and are prone to serious errors when applied to large and divergent biological sequences. The success of this project will not only make significant contribution to the relevant research fields, but also help achieve goals in certain real-life biological research projects which are unique and important to Australia.
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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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