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
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
Discovery Early Career Researcher Award - Grant ID: DE180100245
Funder
Australian Research Council
Funding Amount
$386,500.00
Summary
Achieving millimetre geodesy with space tie satellites. This project aims to implement the completely new concept of observing artificial satellites with radio telescopes, realising a so-called space tie. Understanding Earth’s changing shape requires measurements with a stability of 0.1 mm per year. Today, geodetic earth observations are used to realise reference points with a precision of five to ten times larger. Using the unique Australian ground infrastructure, current observational and oper ....Achieving millimetre geodesy with space tie satellites. This project aims to implement the completely new concept of observing artificial satellites with radio telescopes, realising a so-called space tie. Understanding Earth’s changing shape requires measurements with a stability of 0.1 mm per year. Today, geodetic earth observations are used to realise reference points with a precision of five to ten times larger. Using the unique Australian ground infrastructure, current observational and operational problems shall be overcome. The intended outcome is to improve the coordinate system of the Earth, which is the basis for a better understanding of Earth serving to fulfil scientific as well as societal demands.Read moreRead less
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
Industrial Transformation Research Hubs - Grant ID: IH120100021
Funder
Australian Research Council
Funding Amount
$2,500,000.00
Summary
Pathways to market: transforming food industry futures through improved sensing, provenance and choice. Pathways to market: transforming food industry futures through improved sensing, provenance and choice. This Research Hub aims to transform the Australian food industry by demonstrating how new knowledge on food production and consumption generated through novel sensing technologies and advanced modelling techniques can be implemented in smart applications to power competitiveness, sustainabil ....Pathways to market: transforming food industry futures through improved sensing, provenance and choice. Pathways to market: transforming food industry futures through improved sensing, provenance and choice. This Research Hub aims to transform the Australian food industry by demonstrating how new knowledge on food production and consumption generated through novel sensing technologies and advanced modelling techniques can be implemented in smart applications to power competitiveness, sustainability and innovation in food value chains.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
Choice models for learning and memory. Life is filled with familiar choices that often require quick decisions about objects in the environment and the contents of memory. This project examines how we learn to make rapid and accurate choices and how we quickly asses the level of confidence we have in recognition decisions based on our memories.