Industrial Transformation Research Hubs - Grant ID: IH210100001
Funder
Australian Research Council
Funding Amount
$2,062,428.00
Summary
ARC Research Hub for Nutrients in a Circular Economy (NiCE). Urban utilities are in need to design resilient wastewater infrastructure to tackle the pressures of urban intensification, waterways pollution and climate change. This Hub aims to transform the wastewater industry with an unprecedented, city-scale circular economy of nutrients based on urine separation and processing at building level, to produce safe and effective liquid fertilisers. By engaging with stakeholders across the value cha ....ARC Research Hub for Nutrients in a Circular Economy (NiCE). Urban utilities are in need to design resilient wastewater infrastructure to tackle the pressures of urban intensification, waterways pollution and climate change. This Hub aims to transform the wastewater industry with an unprecedented, city-scale circular economy of nutrients based on urine separation and processing at building level, to produce safe and effective liquid fertilisers. By engaging with stakeholders across the value chain, this Hub expects to bring two urine processing technologies to commercial readiness, and to produce new regulations and business models for the circular economy. This will add resilience to the wastewater and urban farming industries, and will create market opportunities for new Australian technologies.Read moreRead less
Engineered graphene-based nanofertilizers to improve crop nutrition. This project seeks to evaluate the unique properties of graphene to more effectively engineer novel fertilizers with properties that can enhance nutrient efficiency and reduce losses to the environment. More efficient and effective fertilizer formulations are needed to improve nutrient use efficiency in agricultural systems globally, and for effective biofortification of staple food crops with essential micronutrients. Nitrogen ....Engineered graphene-based nanofertilizers to improve crop nutrition. This project seeks to evaluate the unique properties of graphene to more effectively engineer novel fertilizers with properties that can enhance nutrient efficiency and reduce losses to the environment. More efficient and effective fertilizer formulations are needed to improve nutrient use efficiency in agricultural systems globally, and for effective biofortification of staple food crops with essential micronutrients. Nitrogen may be lost from soil through leaching and gaseous losses to the atmosphere. Phosphorus, as well as copper, manganese and zinc, are prone to reactions in soils and during manufacturing which reduces their effectiveness.Read moreRead less
Nutrient generation from rural land and delivery to streams in the Sydney Drinking Water Catchments. The Sydney Catchment Authority must manage pollution arising from land within its catchments. There have been few local studies of nutrient losses from rural land, the major land use, and the understanding of some important processes involved in nutrient generation and delivery is weak. Therefore model predictions are uncertain. This project will quantify nutrient losses from key land uses, ev ....Nutrient generation from rural land and delivery to streams in the Sydney Drinking Water Catchments. The Sydney Catchment Authority must manage pollution arising from land within its catchments. There have been few local studies of nutrient losses from rural land, the major land use, and the understanding of some important processes involved in nutrient generation and delivery is weak. Therefore model predictions are uncertain. This project will quantify nutrient losses from key land uses, evaluate alternative loss pathways, and provide insight into the effects of scale, providing a foundation for improved modelling of nutrient sources and transport. The outcome will be the capacity to prioritise land uses and parts catchments for remedial action, whilst providing a modelling approach relevant to the SCA and other catchment managers.Read moreRead less
Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical ....Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical information, such as encryption keys, through timing channels. This should prevent sophisticated attacks on public clouds, mobile devices and military-grade cross-domain devices.Read moreRead less
Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramat ....Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramatically benefit Australian people and government, especially for the Australian ICT industry for commercializing the research outputs. Read moreRead less
Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH200100023
Funder
Australian Research Council
Funding Amount
$4,950,000.00
Summary
ARC Research Hub for Innovative Nitrogen Fertilisers and Inhibitors. This Hub aims to transform agriculture by delivering a new class of nitrogen (N) fertilisers and inhibitors designed to stem the 50-80% losses to the environment in current products. It is intended to generate new knowledge and valuable intellectual property in controlled released and coated N fertiliser products using a novel co-design process involving representatives of the whole value chain from product design through to va ....ARC Research Hub for Innovative Nitrogen Fertilisers and Inhibitors. This Hub aims to transform agriculture by delivering a new class of nitrogen (N) fertilisers and inhibitors designed to stem the 50-80% losses to the environment in current products. It is intended to generate new knowledge and valuable intellectual property in controlled released and coated N fertiliser products using a novel co-design process involving representatives of the whole value chain from product design through to validation and adoption. The project estimates possible 20% gains in efficiency of N use, delivering large costs savings, improved productivity, increased profitability and decreased environmental impacts, helping the Australian food and agribusiness sector to reach its 2030 target of $100B value added.Read moreRead less
Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.Read moreRead less
Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human expl ....Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human explicit and implicit interest domains. The expected results of this application will not only maintain Australia's leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as cyber security, healthcare, and e-Commerce.Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less