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Research Topic : Capacity Building
Socio-Economic Objective : Expanding Knowledge in Technology
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP200102497

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    Non-contact Integrity Assessment of Façade Panels of High-rise Buildings. Disintegration of the external façade (with tiles, plates, etc.) of high-rise buildings presents a great challenge and a threat to community. This project develops fundamental knowledge and algorithms that underpin the deployment of a new technique for fast and automated quantitative integrity assessment of façade units of high-rise buildings, integrating mechanisms of directional acoustic waves, vibro-acoustics of façade .... Non-contact Integrity Assessment of Façade Panels of High-rise Buildings. Disintegration of the external façade (with tiles, plates, etc.) of high-rise buildings presents a great challenge and a threat to community. This project develops fundamental knowledge and algorithms that underpin the deployment of a new technique for fast and automated quantitative integrity assessment of façade units of high-rise buildings, integrating mechanisms of directional acoustic waves, vibro-acoustics of façade tiles or panels, laser sensing technology, deep learning algorithms and drone technology. Outcomes of this project are critical for implementing the new technology for enhanced safety to community and the development of new procedures for driving down maintenance costs of the external façade of high-rise buildings.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210103631

    Funder
    Australian Research Council
    Funding Amount
    $355,331.00
    Summary
    AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d .... AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.
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    Funded Activity

    Discovery Projects - Grant ID: DP140102003

    Funder
    Australian Research Council
    Funding Amount
    $350,000.00
    Summary
    New generation nanostructured coatings with combined control of spectral and angular emissivity. The aim of this project is to generate a complete scientific understanding of a new generation of hybrid, tri-layered, optically-selective coatings. The new design paradigm combines the very different attributes of smooth and nanostructured layers so that superior and simultaneous control of both spectral and angular properties of light can be achieved. Existing theory will be extended so that quanti .... New generation nanostructured coatings with combined control of spectral and angular emissivity. The aim of this project is to generate a complete scientific understanding of a new generation of hybrid, tri-layered, optically-selective coatings. The new design paradigm combines the very different attributes of smooth and nanostructured layers so that superior and simultaneous control of both spectral and angular properties of light can be achieved. Existing theory will be extended so that quantitative analyses of these new systems and other hybrids become possible and new and improved fabrication techniques will be developed. The work will unlock new technological possibilities for coating performance and application and is likely to be associated with significant improvements in energy conservation and generation.
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    Funded Activity

    Linkage Projects - Grant ID: LP150101052

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    Machine Learning for Fracture Risk Assessment from Simple Radiography. This project aims to develop a novel, reliable, low-cost system to detect poor bone health and assess fracture risk to help to prevent and manage osteoporosis-related fractures. Currently, osteoporosis-related fractures cost our health system millions of dollars annually and costs are increasing with our ageing population. Early detection of poor bone health will improve the effectiveness of preventive measures and ease this .... Machine Learning for Fracture Risk Assessment from Simple Radiography. This project aims to develop a novel, reliable, low-cost system to detect poor bone health and assess fracture risk to help to prevent and manage osteoporosis-related fractures. Currently, osteoporosis-related fractures cost our health system millions of dollars annually and costs are increasing with our ageing population. Early detection of poor bone health will improve the effectiveness of preventive measures and ease this burden. Current methods include unreliable, crude clinical and visual guides that suggest osteoporosis screening. The project plans to develop a novel system by applying machine learning algorithms to radiology data which is commonly captured for diagnosing other conditions.
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