Industrial Transformation Training Centres - Grant ID: IC180100008
Funder
Australian Research Council
Funding Amount
$3,981,223.00
Summary
ARC Training Centre for Multiscale 3D Imaging, Modelling and Manufacturing. The ARC Training Centre for Multiscale 3D Imaging, Modelling and Manufacturing aims to connect the detailed microscopic characteristics of materials with their macroscopic properties and design characteristics of natural and manufactured structures. It will train a new generation of researchers and practitioners in the emerging discipline of Digital Materials. The approach allows optimisation at all scales, enabling cost ....ARC Training Centre for Multiscale 3D Imaging, Modelling and Manufacturing. The ARC Training Centre for Multiscale 3D Imaging, Modelling and Manufacturing aims to connect the detailed microscopic characteristics of materials with their macroscopic properties and design characteristics of natural and manufactured structures. It will train a new generation of researchers and practitioners in the emerging discipline of Digital Materials. The approach allows optimisation at all scales, enabling cost reductions and performance enhancements in key industries, including Oil, Gas and Energy Resources, Medical Technologies, and Advanced Manufacturing. The Centre expects to reduce the time needed in the prototyping cycle and product development, increasing industry’s capacity for accelerated innovation. The developments will build world-class Australian capabilities for developing high-value scaleable production of bespoke products and optimised process design.Read moreRead less
Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algori ....Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algorithms for applied researchers. This project benefits not only advanced manufacturing by finding optimal stopping time for wood panel compression, but also superior forecasting for mortality in demography, climate data in environmental science, asset returns in finance, and electricity consumption in economics. Read moreRead less
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this te ....ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this team with the foremost international authorities and leading industry players in the area of sensor networks. This research network will guide collaborative research that will ensure Australia to play a world leading role in sensor network development and implementation.
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Reconceiving Machine Learning. The proposed research will develop a new way to consider problems to which machine learning can be applied. Machine learning is crucial enabler of the digital economy. The research will provide better opportunities for Australian industry to gain a competitive advantage with machine learning technology. The framework developed will enable better opportunities for collaborative research and will build and strengthen international linkages.
Special Research Initiatives - Grant ID: SR0566892
Funder
Australian Research Council
Funding Amount
$220,000.00
Summary
The EarthByte software and database system. Earth processes over geological timescales cannot be understood outside of a plate tectonic context. However, no standard tool exists to explore the causes and effects of lithosphere-mantle interaction in accordance with past plate configurations. Our aim is to develop a Palaeo-Geographic Information System called EarthByte that will connect the open source and architecture-independent GPlates and GMT software, and implement XML-based service interfac ....The EarthByte software and database system. Earth processes over geological timescales cannot be understood outside of a plate tectonic context. However, no standard tool exists to explore the causes and effects of lithosphere-mantle interaction in accordance with past plate configurations. Our aim is to develop a Palaeo-Geographic Information System called EarthByte that will connect the open source and architecture-independent GPlates and GMT software, and implement XML-based service interfaces and databases. EarthByte will create the foundation for an e-geoscience framework for grid-based data access and Earth process modelling by linking geological and geophysical observations to palaeogeographic models for constraining mantle convection and lithospheric deformation.Read moreRead less
Biofocussed Prostate Cancer RadioTherapy (BiRT): A Personalised Approach To Delivering The Right Dose To The Right Place
Funder
National Health and Medical Research Council
Funding Amount
$753,565.00
Summary
We propose a new approach to treating prostate cancer with radiotherapy to move from the standard whole prostate treatment to a personalised treatment that varies radiation intensity throughout the prostate. We will mathematically combine features that influence radiotherapy effect from advanced imaging, clinical and biopsy information. This model will map out the radiotherapy dose required at each part of the prostate, to maximise killing of the cancer whilst minimising harm to normal tissue
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less
Special Research Initiatives - Grant ID: SR0354729
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
Smart Use of Information Technologies (SUITs). The SUITs network will develop critical mass in world-class, leading-edge research into the smart use of information and communication technology (ICT) through integration of research within the dispersed Australian ICT research community and through facilitating international linkages. The network will undertake research applicable in key sectors including the health, education, service, knowledge and media industries. The aim is to establish a h ....Smart Use of Information Technologies (SUITs). The SUITs network will develop critical mass in world-class, leading-edge research into the smart use of information and communication technology (ICT) through integration of research within the dispersed Australian ICT research community and through facilitating international linkages. The network will undertake research applicable in key sectors including the health, education, service, knowledge and media industries. The aim is to establish a higher order of coordination and collaboration in research into ICT applications.
The feasibility study proposed will engage key stakeholders, refine research goals and investigate linkage mechanisms to improve Australia's ICT research and its contribution to economic and social well-being.
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