Software Defined Networking: Transforming Emergency Operations. The project aims to improve the effectiveness and efficiency of Australia's emergency operations, for example, bushfire and rescue missions, by providing robust and integrated communications systems for police and the emergency services. Emergency communications systems are currently fragmented by the different technologies, creating disconnected islands of information. The project aims to provide techniques that allow multiple wire ....Software Defined Networking: Transforming Emergency Operations. The project aims to improve the effectiveness and efficiency of Australia's emergency operations, for example, bushfire and rescue missions, by providing robust and integrated communications systems for police and the emergency services. Emergency communications systems are currently fragmented by the different technologies, creating disconnected islands of information. The project aims to provide techniques that allow multiple wireless technologies to communicate seamlessly using modern software-defined networking solutions.Read moreRead less
ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this te ....ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this team with the foremost international authorities and leading industry players in the area of sensor networks. This research network will guide collaborative research that will ensure Australia to play a world leading role in sensor network development and implementation.
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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
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
Active Team – Examining An Online Social Networking Intervention To Increase Physical Activity In Controlled (RCT) And Ecological (ET) Settings
Funder
National Health and Medical Research Council
Funding Amount
$814,041.00
Summary
Lifestyle diseases, such as heart disease and diabetes, are key health problems facing Australia. Effective, low-cost, mass-reach physical activity interventions are urgently needed. This project uses online social networks to deliver an innovative physical activity intervention. This project will determine how effective the software is in changing people’s lifestyle over 12 months, and whether viral marketing techniques can be used to disseminate the program on a mass scale.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE200100071
Funder
Australian Research Council
Funding Amount
$535,000.00
Summary
Photonic Chip Integration Facility. This project will create a Photonic Chip Integration Facility responding to newly emerging global trends towards low loss waveguides and wider coverage of the optical spectrum.
The tool will grow ultrahigh quality silicon nitride and oxide thin films in a manner that is compatible with electronics and other delicate materials, balancing flexibility for materials exploration with reliability and repeatability required for photonic chip systems research. The pr ....Photonic Chip Integration Facility. This project will create a Photonic Chip Integration Facility responding to newly emerging global trends towards low loss waveguides and wider coverage of the optical spectrum.
The tool will grow ultrahigh quality silicon nitride and oxide thin films in a manner that is compatible with electronics and other delicate materials, balancing flexibility for materials exploration with reliability and repeatability required for photonic chip systems research. The proposed facility will support Australian researchers from diverse disciplines spanning broadband networks, sensing, quantum technology, materials science, and beyond while providing a clear path for translating discoveries out of the lab towards scale up industrial manufacture
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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
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
Semantic change detection through large-scale learning. This project aims to develop technologies which understand the content of images before higher-level analysis is performed. This approach is intended to allow more accurate and reliable decisions to be made using automated image analysis than has previously been possible. The project will particularly investigate the detection of change in the contents of an image.