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
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.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
Early Career Industry Fellowships - Grant ID: IE230100380
Funder
Australian Research Council
Funding Amount
$390,574.00
Summary
Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error a ....Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error and uncertainty in forensic science and an accessible online dashboard for visualising known error rates in forensic disciplines. The knowledge gained from the project will help forensic experts to calibrate how they present their conclusions to courts for improved comprehension and evaluation of forensic evidence.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0346515
Funder
Australian Research Council
Funding Amount
$507,000.00
Summary
Fluorescence Detector for the Australian National Beamline Facility. X-ray absorption spectroscopy (XAS) is an extremely important synchrotron radiation tool for determining the local structure around an X-ray absorbing atom. This has many applications in the study of materials, minerals, metal complexes, and metalloproteins and can often be used to obtain information that is not available by other techniques, because structural information can be obtained in the solid or solution state and in ....Fluorescence Detector for the Australian National Beamline Facility. X-ray absorption spectroscopy (XAS) is an extremely important synchrotron radiation tool for determining the local structure around an X-ray absorbing atom. This has many applications in the study of materials, minerals, metal complexes, and metalloproteins and can often be used to obtain information that is not available by other techniques, because structural information can be obtained in the solid or solution state and in mixtures. The current proposal is aimed at introducing new technology into the Australian National Beamline Facility that will greatly improve the quality and quantity of experiments that can be performed and extend studies into dilute solutions and protein samples.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100073
Funder
Australian Research Council
Funding Amount
$174,627.00
Summary
Australian Contribution to CERN Large Hadron Collider Experiment Upgrade. Australian contribution to CERN large hadron collider experiment upgrade: The discovery of the Higgs Boson with the ATLAS experiment at the CERN laboratory's large hadron collider, has been a highlight for Australian science. Scientists will build upon the foundation of the Higgs discovery to further probe the nature of matter at the finest scales and highest energies. Detailed measurements of the Higgs characteristics wil ....Australian Contribution to CERN Large Hadron Collider Experiment Upgrade. Australian contribution to CERN large hadron collider experiment upgrade: The discovery of the Higgs Boson with the ATLAS experiment at the CERN laboratory's large hadron collider, has been a highlight for Australian science. Scientists will build upon the foundation of the Higgs discovery to further probe the nature of matter at the finest scales and highest energies. Detailed measurements of the Higgs characteristics will determine if it is as predicted by the Standard Model or whether it admits a variation, signalling new physics. The upgrade in this project will provide for such detailed measurements. It will also allow sensitive probes of new physics, searching for new particles or unexpected interactions.Read moreRead less
Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits ....Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits such as understanding how people operate so effectively in real environments, when even the most powerful computers struggle to handle the complexities of everyday learning problems.Read moreRead less
Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time ....Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time, and confidence, suitable for application to computerized testing scenarios. The models and testing methods validated in the laboratory will be refined for application in eyewitness memory settings, facilitating better evaluation of identification evidence, and potentially reducing wrongful convictions.Read moreRead less