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Australian State/Territory : QLD
Status : Active
Research Topic : generic application
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP240103068

    Funder
    Australian Research Council
    Funding Amount
    $500,610.00
    Summary
    Rigorous Privacy Compliance in Modern Application Ecosystems. Modern network applications such as mobile applications and browser extensions have become the primary gateways for consumers to access the Internet in today’s digital landscape. This project aims to address privacy issues in these ecosystems by developing a new privacy-compliance assessment framework. The framework will evaluate the current privacy practices of application ecosystems, enabling users and developers in Australia and wo .... Rigorous Privacy Compliance in Modern Application Ecosystems. Modern network applications such as mobile applications and browser extensions have become the primary gateways for consumers to access the Internet in today’s digital landscape. This project aims to address privacy issues in these ecosystems by developing a new privacy-compliance assessment framework. The framework will evaluate the current privacy practices of application ecosystems, enabling users and developers in Australia and worldwide to reliably identify potential privacy risks and issues on their applications. The intended outcomes should endow data controllers with the capability of evidencing their compliance of data protection legislations such as Australia Privacy Act 1988 and EU General Data Protection Regulation (GDPR).
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    Active Funded Activity

    Industrial Transformation Research Hubs - Grant ID: IH210100001

    Funder
    Australian Research Council
    Funding Amount
    $2,062,428.00
    Summary
    ARC Research Hub for Nutrients in a Circular Economy (NiCE). Urban utilities are in need to design resilient wastewater infrastructure to tackle the pressures of urban intensification, waterways pollution and climate change. This Hub aims to transform the wastewater industry with an unprecedented, city-scale circular economy of nutrients based on urine separation and processing at building level, to produce safe and effective liquid fertilisers. By engaging with stakeholders across the value cha .... ARC Research Hub for Nutrients in a Circular Economy (NiCE). Urban utilities are in need to design resilient wastewater infrastructure to tackle the pressures of urban intensification, waterways pollution and climate change. This Hub aims to transform the wastewater industry with an unprecedented, city-scale circular economy of nutrients based on urine separation and processing at building level, to produce safe and effective liquid fertilisers. By engaging with stakeholders across the value chain, this Hub expects to bring two urine processing technologies to commercial readiness, and to produce new regulations and business models for the circular economy. This will add resilience to the wastewater and urban farming industries, and will create market opportunities for new Australian technologies.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210100640

    Funder
    Australian Research Council
    Funding Amount
    $425,912.00
    Summary
    A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac .... A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP210200733

    Funder
    Australian Research Council
    Funding Amount
    $397,662.00
    Summary
    Innovations in Demographic Modelling for Government Analysis and Planning. This project aims to create innovative and cutting-edge demographic models to better meet the needs of practitioners and researchers. Together with the partner organisations, Commonwealth Treasury and the Australian Bureau of Statistics, it will focus on creating more accurate and fit-for-purpose forecasting methods for Australian fertility, mortality, and migration, including a policy scenario model to produce population .... Innovations in Demographic Modelling for Government Analysis and Planning. This project aims to create innovative and cutting-edge demographic models to better meet the needs of practitioners and researchers. Together with the partner organisations, Commonwealth Treasury and the Australian Bureau of Statistics, it will focus on creating more accurate and fit-for-purpose forecasting methods for Australian fertility, mortality, and migration, including a policy scenario model to produce population projections by visa/citizenship category and Australians overseas. Expected outcomes of this project include improved forecasting methods reported in open-access papers, user-friendly forecasting software and tools for the partner organisations, and a stronger relationship between researchers and practitioners.
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    Showing 1-4 of 4 Funded Activites

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