Developing group-based elicitation methods to improve decision making. This project aims to develop an elicitation methodology enabling multiple members of a team to contribute to the same technical problem - enabling expertise to be accurately combined while avoiding group and individual sources of bias. Good elicitation methods minimise bias in estimates and forecasts - which otherwise erode value and lead to sub-optimal decision making. Existing methods, however, ignore group structures; that ....Developing group-based elicitation methods to improve decision making. This project aims to develop an elicitation methodology enabling multiple members of a team to contribute to the same technical problem - enabling expertise to be accurately combined while avoiding group and individual sources of bias. Good elicitation methods minimise bias in estimates and forecasts - which otherwise erode value and lead to sub-optimal decision making. Existing methods, however, ignore group structures; that is that decisions made by, or on, the advice of teams have different characteristics than individual decisions and often preclude the use of methods designed to limit individuals' biases. By encoding the method into a computerised tool the project will assist public and private sector enterprises to improve group decision making.Read moreRead less
ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environme ....ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environments. EII will address 3 tightly coupled research themes: Ability to interoperate across existing heterogenous platforms & applications; Efficient processing of very large data sets; Technology adoption & impact. Generic results will be applicable to e-science and large business information systems installations.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100017
Funder
Australian Research Council
Funding Amount
$3,703,664.00
Summary
ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource ....ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource attributes, maximising value ‘on the fly’. Benefits will include increasing certainty on product quality and maximising throughput and recovery. Outcomes will include new tools to rapidly model geological and geometallurgical uncertainty with sensor inputs, to track the resource to product and enhance interpretation.Read moreRead less
Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result giv ....Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result given the input data in a short amount of time. The expected outcomes would support the construction of reliable and accurate computer vision-based systems, such as large-scale 3-D reconstruction from photo collections, self-driving cars and domestic robots.Read moreRead less
Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including comm ....Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including communications and navigational satellites, in Earth’s orbit from collisions and covert sabotage. Increased space use by government and civilian agencies opens up opportunities for the space industry. This project is expected to develop Australia’s space surveillance capabilities, protect space assets and capture a growing market.Read moreRead less
Hydrogen generation by subsurface iron mineral transformations. Aim
The aim of this project is to elucidate key factors responsible for natural hydrogen generation in Australian subsurface environments.
Significance
Large amounts of this valuable resource are produced naturally with estimates of production rates of this “gold” hydrogen at least 100 times the annual demand for this critical resource.
Expected Outcomes
Based on improved understanding of the source of natural hydrogen, predictive ....Hydrogen generation by subsurface iron mineral transformations. Aim
The aim of this project is to elucidate key factors responsible for natural hydrogen generation in Australian subsurface environments.
Significance
Large amounts of this valuable resource are produced naturally with estimates of production rates of this “gold” hydrogen at least 100 times the annual demand for this critical resource.
Expected Outcomes
Based on improved understanding of the source of natural hydrogen, predictive tools will be developed that will assist in assessing the viability in Australia of hydrogen exploration and engineered retrieval.
Benefits
Ready access to naturally produced hydrogen could enable Australia to replace hydrogen that is currently generated via the use of unabated hydrocarbons.Read moreRead less
Towards an integrated model of reasoning and reasoning development. This project aims to identify the core cognitive processes that underlie different forms of reasoning and how they develop. The project intends to use a signal detection framework to derive detailed computational models of reasoning which can then be tested through Bayesian computational modelling as well as the first systematic investigation of developmental change in reasoning processes. Expected outcomes include a more princi ....Towards an integrated model of reasoning and reasoning development. This project aims to identify the core cognitive processes that underlie different forms of reasoning and how they develop. The project intends to use a signal detection framework to derive detailed computational models of reasoning which can then be tested through Bayesian computational modelling as well as the first systematic investigation of developmental change in reasoning processes. Expected outcomes include a more principled and comprehensive computational model of reasoning in both adults and children. The project should provide significant benefits by helping to resolve long-standing debates about how humans reason complex arguments relevant to everyday lives and guide development of more effective methods for teaching reasoning.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100235
Funder
Australian Research Council
Funding Amount
$280,000.00
Summary
Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure wil ....Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure will accelerate the pace of surveillance research and development in Australia, enhancing the competitiveness of both Australia's researchers and the businesses that will commercialise these researchers' discoveries.Read moreRead less