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
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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Special Research Initiatives - Grant ID: SR0354575
Funder
Australian Research Council
Funding Amount
$30,000.00
Summary
Earth and Ocean Informatics and Technology Network (EON-ITnet). Sustainable resource exploration and mining onshore, as well as marine planning, exploration, and defence depend on effective cross-disciplinary investigation, sharing of expertise and technologies for integration and computational analysis of multidimensional data spaces. EON-ITNET will cross-fertilise the use of artificial intelligence, advanced computing and smart information sharing for management, analysis, visualisation and me ....Earth and Ocean Informatics and Technology Network (EON-ITnet). Sustainable resource exploration and mining onshore, as well as marine planning, exploration, and defence depend on effective cross-disciplinary investigation, sharing of expertise and technologies for integration and computational analysis of multidimensional data spaces. EON-ITNET will cross-fertilise the use of artificial intelligence, advanced computing and smart information sharing for management, analysis, visualisation and metadata modelling between these traditionally separate research groups, with the outcome of improving research efficiency and lowering costs. EON-ITNET will form an alliance with the Caltech-based GeoFramework, which is advancing a novel object-oriented data analysis environment, binding community software for Earth visualisation and simulation to 4D data bases.Read moreRead less
Tailoring composite propellers for reduced sound radiation. This project aims to explore the generation of noise by composite propellers and to use this understanding to tailor the composite properties to reduce underwater noise. Propellers are a harmful source of noise in the marine environment, disturbing animal behaviour, revealing the location of naval vessels and interfering with sonar operation. Adaptive composite propellers are potentially quieter than metal propellers, as well as offerin ....Tailoring composite propellers for reduced sound radiation. This project aims to explore the generation of noise by composite propellers and to use this understanding to tailor the composite properties to reduce underwater noise. Propellers are a harmful source of noise in the marine environment, disturbing animal behaviour, revealing the location of naval vessels and interfering with sonar operation. Adaptive composite propellers are potentially quieter than metal propellers, as well as offering improvements in efficiency and fuel consumption. The aims of this project are to understand the physical mechanisms associated with composite propeller noise generation. The outcomes are intended to provide advanced numerical capabilities that will support the development of quieter marine propeller designs to improve defence capability and the acoustic environment for marine mammals.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
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.
An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will r ....An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will rectify this situation by using representation theory to transform combinatorial group theory into linear algebra, allowing for the application of advanced methods of numeric approximation. This will provide a better understanding of how bacteria evolve and improve our ability to manage their impact.Read moreRead less
Prediction of radiated noise from marine propellers. Underwater noise radiated from marine vessels is a significant problem for research, fishing and military vessels, and is a major source of pollution in the marine environment. The major source contributing to underwater noise is due to the propeller. This work will develop numerical models with experimental validation that can accurately predict the sources of noise generated by marine propellers and acoustic signatures of marine vessels due ....Prediction of radiated noise from marine propellers. Underwater noise radiated from marine vessels is a significant problem for research, fishing and military vessels, and is a major source of pollution in the marine environment. The major source contributing to underwater noise is due to the propeller. This work will develop numerical models with experimental validation that can accurately predict the sources of noise generated by marine propellers and acoustic signatures of marine vessels due to propeller motion. This work has great significance for Australia’s construction and military maritime industries. The technologies developed in this project are also applicable to rotors in other industries such as in aircraft, helicopters and wind turbines.Read moreRead less