Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the ....Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the early detection and warning of cyberbullying and approach open a new way to discover interaction patterns with a large number of participants over evolving and complex social networks.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE180100158
Funder
Australian Research Council
Funding Amount
$348,026.00
Summary
A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and ....A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and evaluation of IoT technologies and services. The project will also serve as a vehicle for the education and training of Australia’s next generation of scholars and engineers, and contribute to Australia’s scientific visibility.Read moreRead less
Omniscient face recognition for uncooperative subjects. The outcomes of this project will enable effective video surveillance technology to be developed for use by law enforcement and national security agencies. It will lead to reliable identification of humans at a distance by automatically detecting and recognising faces, for use in counter-terrorism surveillance and commercial robot-human interfaces.
Learned Academies Special Projects - Grant ID: LA170100011
Funder
Australian Research Council
Funding Amount
$170,000.00
Summary
The use of big data for social policy: benefits and risks. This project aims to investigate the benefits and risks of using ‘big data’ and analytics for social policy. Drawing on documentary sources and interviews with experts and stakeholders, the project will use five case studies to examine the capability, underlying assumptions and possible impacts of such techniques. The project will bring together a multi-disciplinary team of social and data scientists to identify the infrastructural, tech ....The use of big data for social policy: benefits and risks. This project aims to investigate the benefits and risks of using ‘big data’ and analytics for social policy. Drawing on documentary sources and interviews with experts and stakeholders, the project will use five case studies to examine the capability, underlying assumptions and possible impacts of such techniques. The project will bring together a multi-disciplinary team of social and data scientists to identify the infrastructural, technical, and social, ethical and legal issues that need to be addressed. The project will define key issues for future research, promote collaboration between the social sciences and big data disciplines, while creating opportunities for building capability for researchers in the social sciences. Read moreRead less
Intelligent Image Retrieval from Distorted and Partial Queries for Rapid Mobile Identification of Pests Threatening Food and the Environment. Pests and diseases are major threats to the Australian food industry and environmental biosecurity. A rapid and mobile pest information retrieval system is critical to prevent a pest becoming established and devastating the region. However, automated insect image retrieval remains an unsolved challenge in the research community. This project addresses the ....Intelligent Image Retrieval from Distorted and Partial Queries for Rapid Mobile Identification of Pests Threatening Food and the Environment. Pests and diseases are major threats to the Australian food industry and environmental biosecurity. A rapid and mobile pest information retrieval system is critical to prevent a pest becoming established and devastating the region. However, automated insect image retrieval remains an unsolved challenge in the research community. This project addresses the fundamental problem of distorted and partial image query in cluttered background in order to achieve pest identification at a much earlier on-site stage. The success of this research will not only make a technical breakthrough towards retrieving objects with movable body parts, but also revolutionise the current pest detection and monitoring process.Read moreRead less
Nature's mechanisms for leaching and remobilising metals. This project aims to understand the chemical and physical processes that govern reactive transport and metal scavenging in rocky environments. Much of Australia's mineral wealth is the result of the interaction of warm fluids with rocks deep in the Earth over geological timescales. The formation of ore deposits is governed by the physical chemistry of mineral dissolution and crystallisation, and by fluid flow through porous rocks and frac ....Nature's mechanisms for leaching and remobilising metals. This project aims to understand the chemical and physical processes that govern reactive transport and metal scavenging in rocky environments. Much of Australia's mineral wealth is the result of the interaction of warm fluids with rocks deep in the Earth over geological timescales. The formation of ore deposits is governed by the physical chemistry of mineral dissolution and crystallisation, and by fluid flow through porous rocks and fractures. This project integrates innovation in geology, chemistry, and mineral engineering, and will deliver mineral-scale reaction models that will increase efficiency of in-situ mining and leaching technologies. Knowledge generated can be applied to improve mineral exploration, mining, and processing, contributing to unlocking billions of dollars’ worth of resources tied up in low grade, mineralogically complex ores.Read moreRead less
Biogeochemistry of ferruginous duricrusts. The project is focussed on the examination and application of microbial iron cycling in the formation of geologically stable, iron duricrusts in tropical regimes. The aim of the project is to develop a site-scale bioremediation strategy for iron ore mines by re-establishing canga, which are ‘ancient’ distinct ecosystems possessing unique plant species rarely found on Earth. This university-industry collaboration aims to produce economic benefits for the ....Biogeochemistry of ferruginous duricrusts. The project is focussed on the examination and application of microbial iron cycling in the formation of geologically stable, iron duricrusts in tropical regimes. The aim of the project is to develop a site-scale bioremediation strategy for iron ore mines by re-establishing canga, which are ‘ancient’ distinct ecosystems possessing unique plant species rarely found on Earth. This university-industry collaboration aims to produce economic benefits for the world’s iron mining industry through advanced training in mining-related research, and through the completion of the mining life cycle by site remediation, enhancing Australia’s position as a global leader in providing innovative solutions to today’s mining challenges.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100030
Funder
Australian Research Council
Funding Amount
$270,000.00
Summary
Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software ....Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software control. The test bed will empower Australian researchers in network technologies and dependent applications (for example, multimedia and security) to collaboratively develop and demonstrate novel ideas at scale. This is expected to benefit Australia by giving our researchers international recognition in this nascent area, and developing a national talent pool for local industry.Read moreRead less
Understanding Dynamic Aspects of Economic Inequality. This project aims to study dynamic aspects of inequality in Australia by exploring the changes in labour and housing market conditions and their relation to the changes in the distribution of income and wealth over the last decade. The project also aims to develop new econometric techniques to examine the factors that are responsible for the changes in the distribution of income and wealth and a range of labour and housing market outcomes. Pa ....Understanding Dynamic Aspects of Economic Inequality. This project aims to study dynamic aspects of inequality in Australia by exploring the changes in labour and housing market conditions and their relation to the changes in the distribution of income and wealth over the last decade. The project also aims to develop new econometric techniques to examine the factors that are responsible for the changes in the distribution of income and wealth and a range of labour and housing market outcomes. Particular attention will be paid to the role of the changes in individual-specific characteristics (such as education, age, employment status, and occupation) and neighbourhood-specific characteristics (such as house prices and population ageing) in producing inequality.Read moreRead less