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data, and develop, test and optimise workflows for CO2 injection monitoring. The project can use the data already recorded as part of the Otway Project and is readily available. To develop a cost
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2024 RTP round - IoT framework for real-time monitoring and control for reused water fit-for-purpose
quality monitoring and control at a large scale suitable for domestic, irrigation, and industrial use or fit-for-use. The proposal aims to develop an IoT framework to continuously monitor the quality
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on leveraging advanced computer vision (CV) and deep learning (DL) techniques to develop a state-of-the-art computer-aided detection and diagnosis (CAD) system for early-stage Alzheimer's disease (AD) detection
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theoretical research on creating adversarial data for process monitoring. 2. Investigate sources of uncertainty in adversarial data. 3. Develop an exhaustive dataset of existing data on concrete corrosion
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RNAi based fungicides for specific fungal diseases of crops. The Hub aims to develop and commercialise an innovative biological alternative to chemical fungicides targeting economically significant
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for remote indigenous communities where the is some good engagement between the clinician and the patient, in mining for remote maintenance, in distance education, and so on. This project may provide
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secondary aim is to develop new algorithms and satellite data products using machine learning based multi-sensor fusion algorithms to combine the products from different sensors on different satellites
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era, this lag prevents planners from generating real-time and real-world responses to ever-increasing and threatening variations surrounding urban areas. This study aims to develop a framework for a
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corresponding to gas emission with the stellar continuum, we will estimate when, where and how the diffuse ionised gas halos were built around galaxies. - Year 1: Develop the algorithm to detect extended ionised