ARC Molecular and Materials Structure Research Network. The Network will build powerful e-Science resources for the structural sciences. Collaborative remote access will be developed for sophisticated instrumentation, including instruments planned for the Replacement Research Reactor and Australian Synchrotron. A structure database service with cross disciplinary content and versatile visualisation and analysis capabilities will further exemplify smart information use. The internet services will ....ARC Molecular and Materials Structure Research Network. The Network will build powerful e-Science resources for the structural sciences. Collaborative remote access will be developed for sophisticated instrumentation, including instruments planned for the Replacement Research Reactor and Australian Synchrotron. A structure database service with cross disciplinary content and versatile visualisation and analysis capabilities will further exemplify smart information use. The internet services will ultimately harness the Grid, enabling linkage into other national and international Grid systems. Encompassing physics, computer science, applied mathematics, chemistry and biochemistry, and catalysing interaction across these disciplines, the MMSN will impact all five National Research Priority 3 goals.Read moreRead less
Creating a national time and frequency network for Australia. This project will develop the means to distribute accurate time and frequency across the Australian continent via an optical fibre network. This network will meet the needs of future telecommunications, science and astronomy projects including the Australian bid for the Square Kilometre Array radio-astronomy project.
Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar ....Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.Read moreRead less
Special Research Initiatives - Grant ID: SR0567321
Funder
Australian Research Council
Funding Amount
$184,781.00
Summary
Real-time Very Long Baseline Interferometry. We will develop a range of software products that are required to implement real-time very long baseline interferometry with the Australia long baseline array. These developments build upon substancial recent infrastructure investments and will place Australia at the forefront of this field. They will enhance our capacity to participate in international collaborations in a range of sciences including astrophysics, spacecraft tracking and geodetic mo ....Real-time Very Long Baseline Interferometry. We will develop a range of software products that are required to implement real-time very long baseline interferometry with the Australia long baseline array. These developments build upon substancial recent infrastructure investments and will place Australia at the forefront of this field. They will enhance our capacity to participate in international collaborations in a range of sciences including astrophysics, spacecraft tracking and geodetic monitoring.Read moreRead less
Developing Evidence Based Strategies For Addressing Childhood Vaccination Rejection
Funder
National Health and Medical Research Council
Funding Amount
$743,927.00
Summary
Parental rejection of vaccines is a global concern that threatens to undermine disease control. A lack of evidence hampers the responses to this complex and persistent problem. We will interview parents who don’t vaccinate their children to learn what influences their decisions. We will then hold community juries and a public engagement process to refine strategies for responding to vaccination rejection that are acceptable to a well informed citizenry, practical and ethically justified.
Discovery Early Career Researcher Award - Grant ID: DE170101514
Funder
Australian Research Council
Funding Amount
$372,000.00
Summary
The control of neuroplasticity in the brain. This project aims to determine how neuroplasticity – the brain’s ability to remodel and make new circuits – is controlled in both excitatory and inhibitory neurons. This capacity, vital for all cognitive functions, diminishes as people age. It is imperative to determine neuroplasticity’s mechanisms and how and why they change, but it is not known how both excitatory and inhibitory neurons contribute to neuroplasticity and how these dynamic alterations ....The control of neuroplasticity in the brain. This project aims to determine how neuroplasticity – the brain’s ability to remodel and make new circuits – is controlled in both excitatory and inhibitory neurons. This capacity, vital for all cognitive functions, diminishes as people age. It is imperative to determine neuroplasticity’s mechanisms and how and why they change, but it is not known how both excitatory and inhibitory neurons contribute to neuroplasticity and how these dynamic alterations are controlled. Understanding neuroplasticity is vital for learning, memory and healthy ageing throughout life.Read moreRead less
Developing a Unified Theory of Episodic Memory. This project aims to develop a model of episodic memory and to apply the model to both adult and child development data. Unlike current approaches, the model is expected to address multiple memory tasks including item recognition, associative recognition, source recognition and cued recall, and also aims to address reaction time data, allowing different sources of interference causing forgetting in adults to be identified. By addressing both encodi ....Developing a Unified Theory of Episodic Memory. This project aims to develop a model of episodic memory and to apply the model to both adult and child development data. Unlike current approaches, the model is expected to address multiple memory tasks including item recognition, associative recognition, source recognition and cued recall, and also aims to address reaction time data, allowing different sources of interference causing forgetting in adults to be identified. By addressing both encoding and retrieval processes, the model can assess how changes in different sources of interference modulate performance through the trajectory of early development. Hierarchical Bayesian estimation aims to enable a simultaneous account of multiple tasks and support future deployment in applied contexts.Read moreRead less
Automated internet warnings to prevent viewing of minor-adult sex images. Since the advent of the internet and digital cameras, the market for child exploitation material (CEM) has boomed. This project aims to explore how the visual appearance of warning messages influences internet users. It plans to conduct a randomised controlled experiment with naïve participants on a real-life website to test the effectiveness of messages designed to discourage viewers of legal ‘barely legal’ pornography. I ....Automated internet warnings to prevent viewing of minor-adult sex images. Since the advent of the internet and digital cameras, the market for child exploitation material (CEM) has boomed. This project aims to explore how the visual appearance of warning messages influences internet users. It plans to conduct a randomised controlled experiment with naïve participants on a real-life website to test the effectiveness of messages designed to discourage viewers of legal ‘barely legal’ pornography. It is anticipated that results will assist policing efforts by indicating whether warnings can be used to dissuade first-time CEM viewers and whether differences exist between harm or deterrent-focused messages.Read moreRead less
An empirically-derived conceptual framework for designing usable and useful wireless mobile applications. The technological challenges posed by mobile computing devices have taken priority over the issues of appropriate use and usability that will ultimately determine their success in real work environments.
This project investigates these issues, particularly the role played by the context of use in the usability and usefulness of mobile applications.
The project's aims will be realised ....An empirically-derived conceptual framework for designing usable and useful wireless mobile applications. The technological challenges posed by mobile computing devices have taken priority over the issues of appropriate use and usability that will ultimately determine their success in real work environments.
This project investigates these issues, particularly the role played by the context of use in the usability and usefulness of mobile applications.
The project's aims will be realised through ethnographic studies of mobile work practice, representative use scenarios and the development of an empirically grounded conceptual framework that can guide the design of usable mobile applications.
The results will increase the successful utilisation of mobile technology by Australian industries.
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Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less