The prediction of sleep/wake behaviour based on physiological and social factors. The prevalence of shiftwork has increased in Australia over the last few decades. Shiftworkers obtain less sleep, have greater difficulty maintaining good relationships, have poorer health, and are more likely to be injured at work than others. Using the largest dataset of its kind, we will substantially contribute to understanding the relationships between work hours, sleep, performance and safety. Ultimately, the ....The prediction of sleep/wake behaviour based on physiological and social factors. The prevalence of shiftwork has increased in Australia over the last few decades. Shiftworkers obtain less sleep, have greater difficulty maintaining good relationships, have poorer health, and are more likely to be injured at work than others. Using the largest dataset of its kind, we will substantially contribute to understanding the relationships between work hours, sleep, performance and safety. Ultimately, the project will answer a question critical to workplace safety - how much time off between shifts is needed to be alert and safe at work? The project will also produce tools to help industry design fatigue-friendly rosters, improving the safety, productivity and general well-being of shiftworkers in Australia and overseas.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
ARC Complex Open Systems Research Network. Complexity is the common frontier in the physical, biological and social sciences. This Network will link specialists in all three sciences through five generic conceptual and mathematical theme activities. It will promote research into how subsystems self-organise into new emergent structures when assembled into an open, non-equilibrium system. Outcomes will include new technologies and software tools and deeper understanding of fundamental questions i ....ARC Complex Open Systems Research Network. Complexity is the common frontier in the physical, biological and social sciences. This Network will link specialists in all three sciences through five generic conceptual and mathematical theme activities. It will promote research into how subsystems self-organise into new emergent structures when assembled into an open, non-equilibrium system. Outcomes will include new technologies and software tools and deeper understanding of fundamental questions in science. An essential function of the network will be introducing researchers end users to new tools and broadening the horizons of graduate students.Read moreRead less
Special Research Initiatives - Grant ID: SR0354693
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
Australian e-Research Grid. The e-Research Grid program will research and implement core Grid technologies on APAC and partner's deployed HPC resources, to underpin a broad range of Australian research. The computer science CIs will form collaborative links with international programs, adapting developments to local circumstances. The applications-domain CIs will leverage those into their scientific simulations and databases, using grid integrative techniques and portals. Many CIs participate in ....Australian e-Research Grid. The e-Research Grid program will research and implement core Grid technologies on APAC and partner's deployed HPC resources, to underpin a broad range of Australian research. The computer science CIs will form collaborative links with international programs, adapting developments to local circumstances. The applications-domain CIs will leverage those into their scientific simulations and databases, using grid integrative techniques and portals. Many CIs participate in other RNs linking to their motivating applications, enhancing prospects for research and integration. They participate in the APAC Grid program, leveraging 75 HPC staff nationally. A key aim is interoperability with "real-world Grids": eg e-learning & e-health programs.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
Systematically model the large-scale complexity of turbulent floods and thin film flows. This project continues development of new models, and computer
simulation, of turbulent flood, river and estuarine flow. The models
will be based systematically upon established turbulence models to
resolve accurately the complex physical processes. The development of
new and robust computer models for thin layers of coating fluid will
aid many industrial processes. We also aim to provide correct ini ....Systematically model the large-scale complexity of turbulent floods and thin film flows. This project continues development of new models, and computer
simulation, of turbulent flood, river and estuarine flow. The models
will be based systematically upon established turbulence models to
resolve accurately the complex physical processes. The development of
new and robust computer models for thin layers of coating fluid will
aid many industrial processes. We also aim to provide correct initial
conditions and boundary conditions for simpler cases of the above
flows. The approach leads to a greater understanding of the range of
applicability of the models through better estimating the errors in the
modelling process. The project develops a fundamental enabling
methodology for engineering and the sciences.
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Investigation and development of robust rule discovery and classification system. This research focuses on a national research priority, namely smart information use. The expected outcomes of the project will greatly advance intelligent system design, such as automatic decision making, fault detection and problem diagnosis, for finance, medical, telecom and many other areas. It has great potential for commercialisation and earning incomes for the future research. The publications will benefit th ....Investigation and development of robust rule discovery and classification system. This research focuses on a national research priority, namely smart information use. The expected outcomes of the project will greatly advance intelligent system design, such as automatic decision making, fault detection and problem diagnosis, for finance, medical, telecom and many other areas. It has great potential for commercialisation and earning incomes for the future research. The publications will benefit the future development of intelligent systems for dealing with missing data. This project directly supports a PhD student and two research assistants who will most likely continue their higher degree study. These contribute to regional tertiary education.Read moreRead less
Learning human activities through low cost, unobtrusive RFID technology. A rapidly growing aged population presents many challenges to Australia's health and aged care services. The outcomes of this project will help aging Australians live in their own homes longer, with greater independence and safety by providing an automated, unobtrusive means for health professionals to monitor activity and intervene as required.
Effective and accurate model dynamics, deterministic and stochastic, across multiple space and time scales. A persistent feature of complex systems in engineering and science is the emergence of macroscopic, coarse grained, coherent behaviour from the interactions of microscopic agents (molecules, cells, grains) and with their environment. In current modeling, ranging from ecology to materials science, the underlying microscopic mechanisms are often known, but the closures to translate microscal ....Effective and accurate model dynamics, deterministic and stochastic, across multiple space and time scales. A persistent feature of complex systems in engineering and science is the emergence of macroscopic, coarse grained, coherent behaviour from the interactions of microscopic agents (molecules, cells, grains) and with their environment. In current modeling, ranging from ecology to materials science, the underlying microscopic mechanisms are often known, but the closures to translate microscale knowledge to a system level macroscopic description are rarely available in closed form. Our novel methodology will explore this stumbling block, and promises to radically change the modeling, exploration and understanding of multiscale complex system behaviour.Read moreRead less