Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven p ....Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven patient group discovery, which could more precisely identify the patient cohorts most likely to benefit from a specific policy; and a model to predict the efficacy of policy options, which could increase the sustainability of the national health system by enabling smarter, more efficient policy decision-making.Read moreRead less
Automatic speech-based assessment of mental state via mobile device. This project aims to create the first mobile, device-based automatic assessment of mental state from acoustic speech. Focusing on novel approaches for eliciting speech, for regression-based scoring of mental state and for longitudinal modelling of speech, the project takes speech processing out of the laboratory and into realistic environments. The project is significant because elicitation approach and longitudinal modelling h ....Automatic speech-based assessment of mental state via mobile device. This project aims to create the first mobile, device-based automatic assessment of mental state from acoustic speech. Focusing on novel approaches for eliciting speech, for regression-based scoring of mental state and for longitudinal modelling of speech, the project takes speech processing out of the laboratory and into realistic environments. The project is significant because elicitation approach and longitudinal modelling have been acknowledged by the research community as challenges that are valuable to investigate, and because conventional regression methods are sub-optimal on ordinal mental state scales. This is significant commercially because mobile devices allow individually tailored, frequent and low-cost mental state assessment. Expected outcomes will include commercial-ready technology, trialled on Australians, accessible to everyone with a mobile device and concentration of Australian research and development capability in a rapidly growing application area.Read moreRead less
Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less
Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of profi ....Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of proficiency testing and continuing education vital for a vibrant, well regulated discipline. In addition, the project will contribute to our knowledge of the pathology assessed in the screening and diagnosis of cancers such as cervical, lung and bladder cancers.Read moreRead less
From economic benefit to social cost: Antecedents of irresponsible gambling. The social impact of gambling is a challenge for policy-makers. Australia's gambling expenditure in 2001 contributed $4.4 billion in tax revenue. This economic benefit however, is offset by significant social costs ($1.8 to $5.6 billion). We will identify when and how distorted memory for previous gambling outcomes and gaming machine accessibility can cause irresponsible gambling. The results can be used to make informe ....From economic benefit to social cost: Antecedents of irresponsible gambling. The social impact of gambling is a challenge for policy-makers. Australia's gambling expenditure in 2001 contributed $4.4 billion in tax revenue. This economic benefit however, is offset by significant social costs ($1.8 to $5.6 billion). We will identify when and how distorted memory for previous gambling outcomes and gaming machine accessibility can cause irresponsible gambling. The results can be used to make informed assessments of the social impact of increasing the accessibility of gambling opportunities on local communities. The results can also be used to understand how gambling that contributes to the economy of a community becomes a social cost.Read moreRead less
Executive functioning, gender, age and medication as predictors of developmental well-being among students with ADHD. This study constructs social-cognitive phenotypes of ADHD, evaluates mental health and investigates ADHD student perceptions of classroom environment and achievement in science as functions of executive functioning, gender, age and medication. The effect of standard psychostimulant intervention and a novel nonpsychostimulant option on executive function, developmental and educati ....Executive functioning, gender, age and medication as predictors of developmental well-being among students with ADHD. This study constructs social-cognitive phenotypes of ADHD, evaluates mental health and investigates ADHD student perceptions of classroom environment and achievement in science as functions of executive functioning, gender, age and medication. The effect of standard psychostimulant intervention and a novel nonpsychostimulant option on executive function, developmental and educational outcomes will be investigated. The expected outcomes will inform more effective teacher professional development, and reduce school problems associated with psychostimulant medication and its illicit distribution by students. The linkage of health and education partners meets a nationally identified need for more effective collaboration to improve education outcomes for ADHD students.Read moreRead less
Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical b ....Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical books. Libraries and legal, social and data science researchers will investigate eBook lending practices and understand their social impacts. The project will identify ways of reforming policy, law, and practice to help libraries fulfil their public interest missions. This project is expected to enable libraries to extract more value from existing public investments.Read moreRead less
X-ray Micro-tomography Validation of HRCT-Based Airway Measurements. This project brings together a newly emergent modality of microscopy in the form of 3D X-ray micro-tomography (XRMT) along with leading-edge image analysis to develop breakthrough science in respiratory research aimed at improving the reliability of high resolution computed tomography (HRCT). The project will develop novel 3D lung image segmentation protocols, a stereotactic registration program allowing 3D matching of XRCT and ....X-ray Micro-tomography Validation of HRCT-Based Airway Measurements. This project brings together a newly emergent modality of microscopy in the form of 3D X-ray micro-tomography (XRMT) along with leading-edge image analysis to develop breakthrough science in respiratory research aimed at improving the reliability of high resolution computed tomography (HRCT). The project will develop novel 3D lung image segmentation protocols, a stereotactic registration program allowing 3D matching of XRCT and HRCT data sets, and a validation protocol for quantitative HRCT analysis of airway disease. These outcomes will allow wider application of HRCT to non-invasively follow the dynamics of pulmonary function.Read moreRead less
Training for Adaptability: The role of errors, exceptions and rules of thumb. This project involving collaboration among three fire services across two states and two universities aims to develop theoretical and evidenced-based error and exceptions training in the prediction of fire behaviour among novices and experts. The project will advance significantly our understanding of ways of adapting knowledge and updating and improving rules of thumb for complex decision-making. An innovative new cri ....Training for Adaptability: The role of errors, exceptions and rules of thumb. This project involving collaboration among three fire services across two states and two universities aims to develop theoretical and evidenced-based error and exceptions training in the prediction of fire behaviour among novices and experts. The project will advance significantly our understanding of ways of adapting knowledge and updating and improving rules of thumb for complex decision-making. An innovative new critical incident recording system will be developed that identifies the cognitive determinants of errors. Tightly controlled laboratory studies will be combined with field studies leading to improved theoretical understanding as well as practical outcomes for the fire services.Read moreRead less
Hardware-based accelerators for real-time machine learning. This project will tackle the challenge of applying real-time machine learning to massive high-frequency data. This project will leverage advancements in machine learning and hardware synthesis to implement computationally complex machine-learning algorithms on hardware-accelerated platforms, avoiding overhead delays incurred by software running on a processor.