Industrial Transformation Training Centres - Grant ID: IC150100019
Funder
Australian Research Council
Funding Amount
$4,571,797.00
Summary
ARC Training Centre for Liquefied Natural Gas Futures. ARC Training Centre for Liquefied Natural Gas Futures. This training centre aims to deliver projects and training to enable future Australian Liquefied Natural Gas (LNG) production from reserves in deep water, at small or remote on-shore locations, with greater efficiency, less environmental impact, and at lower cost than currently possible. This should be accomplished via research projects undertaken by the PhD students and research fellows ....ARC Training Centre for Liquefied Natural Gas Futures. ARC Training Centre for Liquefied Natural Gas Futures. This training centre aims to deliver projects and training to enable future Australian Liquefied Natural Gas (LNG) production from reserves in deep water, at small or remote on-shore locations, with greater efficiency, less environmental impact, and at lower cost than currently possible. This should be accomplished via research projects undertaken by the PhD students and research fellows with guidance from the centre’s industrial partners. The centre’s expected legacy is a unique research and training facility, designed for future integration into a microscale LNG plant. The anticipated research and training outcomes will help to ensure Australia plays a leading role in future global LNG developments.Read moreRead less
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.
ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less
Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expect ....Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expected outcomes include protocol to accurately monitor emissions, models to predict emission under various conditions, and mitigation guideline for typical plant configurations. The anticipated benefit is a significant reduction in GHG emissions from urban water industry and support it to meet net-zero-emission goal by 2050.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100422
Funder
Australian Research Council
Funding Amount
$386,637.00
Summary
Feasible quantification of greenhouse gas emitted from wastewater treatment. This project aims to develop an accurate and practical approach to quantify greenhouse gas (GHG) emissions from wastewater treatment. Australian water utilities have pledged to net-zero emissions. However, most utilities do not know its actual emissions due to lack of feasible quantification method. This project will apply an interdisciplinary approach via mechanism investigations, mathematical modelling, and field work ....Feasible quantification of greenhouse gas emitted from wastewater treatment. This project aims to develop an accurate and practical approach to quantify greenhouse gas (GHG) emissions from wastewater treatment. Australian water utilities have pledged to net-zero emissions. However, most utilities do not know its actual emissions due to lack of feasible quantification method. This project will apply an interdisciplinary approach via mechanism investigations, mathematical modelling, and field works to develop and validate a new feasible quantification method. This project will also advance knowledge on GHG emissions to guide quantification design. The outcomes will be translated into industry protocols and disseminated into industry. The outcomes provide timely support to water sector on its pathway to net-zero.Read moreRead less
Special Research Initiatives - Grant ID: SR0354735
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
Australian Network on Microelectronics, Optoelectronics and Microelectromechanical Systems. The Network will encompass semiconductor microelectronics, optoelectronics, sensors and microelectromechanical systems (MEMS). Fundamental research in these areas enables the technological advances that underpin rapidly developing industries such as information and telecommunications technologies, defence, aerospace, medicine, and remote sensing. Exciting challenges exist in designing new devices that exp ....Australian Network on Microelectronics, Optoelectronics and Microelectromechanical Systems. The Network will encompass semiconductor microelectronics, optoelectronics, sensors and microelectromechanical systems (MEMS). Fundamental research in these areas enables the technological advances that underpin rapidly developing industries such as information and telecommunications technologies, defence, aerospace, medicine, and remote sensing. Exciting challenges exist in designing new devices that exploit unique semiconductor systems and technologies. By sharing capabilities and resources (both capital and human), the network will enable the issues associated with such novel materials and devices to be addressed in a targeted manner. The network will also guarantee the ongoing future of research in the area by actively involving early career researchers and postgraduate students.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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Model guided design of advanced microalgae production systems. This project aims to improve the efficiency of advanced single-celled green algae (microalgae) production systems which can produce a wide range of high-value products including renewable fuels and animal feeds. Such systems are able to expand photosynthetic capacity onto non-arable land using carbon dioxide and saline water. However, production efficiencies and costs are currently limited by the ability to capture and distribute lig ....Model guided design of advanced microalgae production systems. This project aims to improve the efficiency of advanced single-celled green algae (microalgae) production systems which can produce a wide range of high-value products including renewable fuels and animal feeds. Such systems are able to expand photosynthetic capacity onto non-arable land using carbon dioxide and saline water. However, production efficiencies and costs are currently limited by the ability to capture and distribute light through these systems effectively. This project aims to optimise methods of light delivery and distribution through photo-bioreactors and high rate ponds. This knowledge is intended to be integrated into advanced modelling tools to enable model-guided design of next-generation high-efficiency systems.Read moreRead less