Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100030
Funder
Australian Research Council
Funding Amount
$270,000.00
Summary
Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software ....Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software control. The test bed will empower Australian researchers in network technologies and dependent applications (for example, multimedia and security) to collaboratively develop and demonstrate novel ideas at scale. This is expected to benefit Australia by giving our researchers international recognition in this nascent area, and developing a national talent pool for local industry.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100213
Funder
Australian Research Council
Funding Amount
$335,000.00
Summary
Optimising the National Benefits From Restoring Environmental Water Flows. The project plans to evaluate strategies that may maximise the national benefits from restoring environmental flows in Australia’s Murray–Darling Basin (MDB). MDB water supply is characterised by prolonged droughts and flood events, and future climatic projections anticipate that these water supply events will intensify. As the uncertainty of future water supply increases, it is important that the volume of water provided ....Optimising the National Benefits From Restoring Environmental Water Flows. The project plans to evaluate strategies that may maximise the national benefits from restoring environmental flows in Australia’s Murray–Darling Basin (MDB). MDB water supply is characterised by prolonged droughts and flood events, and future climatic projections anticipate that these water supply events will intensify. As the uncertainty of future water supply increases, it is important that the volume of water provided by the portfolio of water rights is known. By examining how decision-makers adapt to water supply uncertainty, optimal management strategies could be determined for watering key ecological assets, trading water between irrigators and the government; and private and public investments.Read moreRead less
Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat ....Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101565
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodol ....Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodologies in finite mixture modelling using skew component distributions to provide better models for handling data with non-normal features (such as skewness, heavy/light tails, and multimodality). Applications may include security intrusion detection, clinical diagnosis and prognosis, and flow and mass cytometry.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100129
Funder
Australian Research Council
Funding Amount
$270,000.00
Summary
Internet of things testbed for creating a Smart City. The Internet of Things Testbed facility replicates the conditions of a city-wide distribution of sensors and data collection applications to model in real time the functioning urban sensing elements of a smart city, translating vast amounts of sensor data into meaningful information and ultimately action.
Economic complexity as a driver of innovation and smart specialisation. This project aims to determine how economic complexity can drive innovation and smart specialisation and how industry can be supported to transition to a more competitive economy. With the downturn of traditional manufacturing, innovation is crucial to create new industries and the jobs of the future. The expected outcomes of this project include high-value industry intelligence in support of product diversification. This sh ....Economic complexity as a driver of innovation and smart specialisation. This project aims to determine how economic complexity can drive innovation and smart specialisation and how industry can be supported to transition to a more competitive economy. With the downturn of traditional manufacturing, innovation is crucial to create new industries and the jobs of the future. The expected outcomes of this project include high-value industry intelligence in support of product diversification. This should provide significant benefits, such as increased international competitiveness, exports, revenue, and economic growth.
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Walking with dinosaurs in the Kimberley: mapping the Cretaceous landscapes of the Dampier Peninsula. The coastline of the Dampier Peninsula, Western Australia, preserves what is arguably one the largest and most significant stretches of dinosaur track-sites in the world. Despite recent National Heritage listing, the majority of these tracksites are largely undocumented, such that their full scientific significance is poorly understood. The aim of this project is to digitally map the dinosaur tra ....Walking with dinosaurs in the Kimberley: mapping the Cretaceous landscapes of the Dampier Peninsula. The coastline of the Dampier Peninsula, Western Australia, preserves what is arguably one the largest and most significant stretches of dinosaur track-sites in the world. Despite recent National Heritage listing, the majority of these tracksites are largely undocumented, such that their full scientific significance is poorly understood. The aim of this project is to digitally map the dinosaur tracksites of the Dampier Peninsula, utilising high-resolution aerial photography with both manned and unmanned aircraft, airborne and hand-held LiDAR imaging, and digital photogrammetry. The results will allow us to construct high-resolution, three-dimensional digital outcrop models of the tracksites, and bring the 130 million-year-old landscapes back to life.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Understanding, measuring and managing the benefits of urban waterways. This project aims to improve understanding of the contribution of urban waterways to enhanced liveability in cities. Australia needs better water resource management and the rapid growth of Australia’s cities places increased importance on managing natural assets in metropolitan areas. The project focuses on clarifying the link between the benefits of waterways and the measurement techniques used by economists, which in turn ....Understanding, measuring and managing the benefits of urban waterways. This project aims to improve understanding of the contribution of urban waterways to enhanced liveability in cities. Australia needs better water resource management and the rapid growth of Australia’s cities places increased importance on managing natural assets in metropolitan areas. The project focuses on clarifying the link between the benefits of waterways and the measurement techniques used by economists, which in turn inform management choices. The project aims to fill an important gap between the psychology and economics disciplines and outputs should significantly improve the way waterways are valued and managed. This is intended to offer benefits for urban residents and to improve the methodologies used for environmental valuation.Read moreRead less
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less