Towards New Functionality in Dairy Ingredients. The Australian dairy industry plays a significant part in the nation’s economy, with almost $3 billion in export revenue in 2016-2017. Powdered dairy products extend shelf life and ease of transport, with >20% annual growth in premium products, such as milk protein concentrates and infant formula powders. This project aims to support the development of value-added dairy powders by investigating the impact of a novel high pressure processing technol ....Towards New Functionality in Dairy Ingredients. The Australian dairy industry plays a significant part in the nation’s economy, with almost $3 billion in export revenue in 2016-2017. Powdered dairy products extend shelf life and ease of transport, with >20% annual growth in premium products, such as milk protein concentrates and infant formula powders. This project aims to support the development of value-added dairy powders by investigating the impact of a novel high pressure processing technology in enhancing the properties of dairy powders and/or introducing new functionality. Successful outcomes will help expand the offering of high value dairy ingredients and thus increase the global competitiveness of Australian dairy manufacturing.Read moreRead less
A Concurrent Multiscale Model for Improved Prediction of Drying Process. This project aims to develop an innovative multiscale model for food drying, which integrates spatial and temporal nonlinear behaviours at different scales. The proposed unifying theory will capture dynamic micro level features and upscale them to macro level features through a concurrent bridging scheme. As cellular elements critically govern the drying process, the fundamental understanding captured through this theory wi ....A Concurrent Multiscale Model for Improved Prediction of Drying Process. This project aims to develop an innovative multiscale model for food drying, which integrates spatial and temporal nonlinear behaviours at different scales. The proposed unifying theory will capture dynamic micro level features and upscale them to macro level features through a concurrent bridging scheme. As cellular elements critically govern the drying process, the fundamental understanding captured through this theory will lead to more accurate prediction of drying kinetics, deformation and quality changes, and hence the development of efficient drying systems. This project will overcome a longstanding research problem and position Australia at the forefront in world drying research to reap substantial economic benefits for Australia.Read moreRead less
Biofilm responses to cold atmospheric plasma . This project is focused on understanding the interaction of cold atmospheric plasmas with biofilms, with the aim of biofilm eradication and ultimately offering an environmentally friendly alternative to current detergents and antibiotics. The research expects to elucidate the fundamental mechanisms of action for breakthrough plasma intervention technologies, which are sufficiently active to cope with the resistant nature of biofilms, yet are of low ....Biofilm responses to cold atmospheric plasma . This project is focused on understanding the interaction of cold atmospheric plasmas with biofilms, with the aim of biofilm eradication and ultimately offering an environmentally friendly alternative to current detergents and antibiotics. The research expects to elucidate the fundamental mechanisms of action for breakthrough plasma intervention technologies, which are sufficiently active to cope with the resistant nature of biofilms, yet are of low energy, do not adversely affect surface properties and critically leave no residual chemistry. This should provide significant benefits by delivering a new method to tackle the ubiquitous problem of biofilm contamination in food, water and medical areas.Read moreRead less
Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the ext ....Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the extent of such biases, and develop models that are both more socially equitable, as well as less prone to expose private data in the learned representations. In doing so, it will make NLP more accessible to new populations of users, and remove socio-technological barriers to NLP uptake.Read moreRead less
Transforming Australian bio-based industries through multiscale modelling. Agricultural and forestry biomass can be converted into feedstocks for production of biofuels and biomaterials via synthetic biology. A key challenge is the complex biomass microstructure renders it highly resistant to conversion, and pretreatment is crucial for enhancing process efficiency. Micro-CT imaging will enable particle characterisation and identification of changes in the fibre composition during pretreatment. T ....Transforming Australian bio-based industries through multiscale modelling. Agricultural and forestry biomass can be converted into feedstocks for production of biofuels and biomaterials via synthetic biology. A key challenge is the complex biomass microstructure renders it highly resistant to conversion, and pretreatment is crucial for enhancing process efficiency. Micro-CT imaging will enable particle characterisation and identification of changes in the fibre composition during pretreatment. This information will be used to create a virtual biomass particle model for an in silico investigation to inform optimal process design. The framework will transform the way biomass is processed, contributing to the growth of the Australian bio-manufacturing industry by making it more productive, profitable and sustainable.Read moreRead less
Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applicatio ....Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applications of significant social, environmental and economic value, such as Location-Aware Service, Environment Monitoring, Augmented Reality, Autonomous Vehicle, and Rapid Emergency Response. The project will enhance Australia's international competitive advantage in forefront of ICT research and technology innovation.Read moreRead less
Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the ....Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the primary limitations of deep learning and will greatly increase its practical application to a range of industrial, cultural or health settings.Read moreRead less
Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approa ....Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approach based on network analysis of database record connectivity. These tools will enable quantifying data quality at scale. Researchers, evidence-based decision-makers in biomedicine, and the analytical or predictive tools that use this data will make more reliable inferences and decisions.Read moreRead less
Deep analytics of non-occurring but important behaviours. This project aims to build a systematic theory for the deep analytics of complex and important occurring and non-occurring behaviours. Behaviours that should occur but do not take place, called non-occurring behaviours (NOB), are widely evident but easily overlooked, such as missed important medical treatments. While often occurring behaviours are focused, such NOB may be associated with significant effects such as a threat to health. Thi ....Deep analytics of non-occurring but important behaviours. This project aims to build a systematic theory for the deep analytics of complex and important occurring and non-occurring behaviours. Behaviours that should occur but do not take place, called non-occurring behaviours (NOB), are widely evident but easily overlooked, such as missed important medical treatments. While often occurring behaviours are focused, such NOB may be associated with significant effects such as a threat to health. This project expects to fill the knowledge gaps in representing, analysing and evaluating NOB complexities and impact, with significant benefits for the evidence-based detection, prediction and risk management of covert NOB applications and their important effects.Read moreRead less
Constraint-based Reasoning for Multi-agent Pathfinding. Automation is a transformative technology for logistics -- using robots to manipulate inventory allows warehouses to be more efficient, and larger-scale, than ever before. But doing this in practice requires efficient, reliable methods for coordinating ever-larger fleets of robots. These problems are extremely difficult, and current approaches either scale poorly or give weak or no guarantees on solution quality. The project will develop t ....Constraint-based Reasoning for Multi-agent Pathfinding. Automation is a transformative technology for logistics -- using robots to manipulate inventory allows warehouses to be more efficient, and larger-scale, than ever before. But doing this in practice requires efficient, reliable methods for coordinating ever-larger fleets of robots. These problems are extremely difficult, and current approaches either scale poorly or give weak or no guarantees on solution quality. The project will develop transformative approaches to multi-agent pathfinding which can handle industrial size problems, and handle all of the complications that arise in practical applications. This will deliver improved cost-effectiveness and productivity to automated warehouse logistics and other agent coordination problems.Read moreRead less