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Field of Research : Software Engineering
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  • Funded Activity

    Discovery Projects - Grant ID: DP0559111

    Funder
    Australian Research Council
    Funding Amount
    $223,000.00
    Summary
    WAVELET-BASED MODELLING AND MODEL PREDICTIVE CONTROL OF COMPLEX MULTIDIMENSIONAL CRYSTALLISATION PROCESSES. The results of this project will directly contribute to a better understanding of crystallisation which is an important unit operation to achieve high purity separations. Many Australian industries for example, mineral processing, sugar processing, pharmaceuticals, etc will benefit from the results in order to enhance optimal operation and control to ensure globally competitive production .... WAVELET-BASED MODELLING AND MODEL PREDICTIVE CONTROL OF COMPLEX MULTIDIMENSIONAL CRYSTALLISATION PROCESSES. The results of this project will directly contribute to a better understanding of crystallisation which is an important unit operation to achieve high purity separations. Many Australian industries for example, mineral processing, sugar processing, pharmaceuticals, etc will benefit from the results in order to enhance optimal operation and control to ensure globally competitive production which is on time, minimize wastes and raw materials and inventories. The leading edge results will increase the contributions of these industries to the Australian economy and our global competitiveness necessary to maintain our culture and the beauty of our environment.
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    Active Funded Activity

    Industrial Transformation Research Hubs - Grant ID: IH170100013

    Funder
    Australian Research Council
    Funding Amount
    $2,962,655.00
    Summary
    ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device .... ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210101348

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an .... Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE170101081

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis t .... Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis to efficiently and precisely analyse large-scale programs according to clients’ needs, thereby allowing compilers to generate safe, reliable and secure code. This project is expected to advance value-flow analysis for industrial-sized software, improve software reliability and security, and benefit Australian software systems and industries.
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