Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less
Practice-based Systematized Nomenclature of Medicine (SNOMED) concept learning for drug-disease precaution early detection and refinement. The outcome of the Systematized Nomenclature of Medicine (SNOMED) concept learning system will help mitigate the impact of Adverse Drug Events hence directly contribute to the National Research Priority promoting and maintaining good health. It will tailor SNOMED knowledge to different clinical settings and provide evidence-based preventative health care. Th ....Practice-based Systematized Nomenclature of Medicine (SNOMED) concept learning for drug-disease precaution early detection and refinement. The outcome of the Systematized Nomenclature of Medicine (SNOMED) concept learning system will help mitigate the impact of Adverse Drug Events hence directly contribute to the National Research Priority promoting and maintaining good health. It will tailor SNOMED knowledge to different clinical settings and provide evidence-based preventative health care. The enabling methodology from this project for building computerised cognitive learning systems will be a frontier technology to enhance smart information use in clinical decision support. It will also contribute to the development of knowledge-based systems. A network version of the developed system will assist doctors working in rural and remote areas with their clinical decision making and prescribing practice.Read moreRead less
Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emer ....Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.Read moreRead less
Ultrashort pulse laser for ultra-hard machine tools processing. This project aims to develop an advanced high-precision ultrashort pulse laser technique for shaping and sharpening cutting tools. It expects to generate new knowledge and new technology in machine tool fabrication using an innovative approach for processing ultra-hard materials. The expected outcome is progressive machining capabilities with higher throughput, significantly reduced production time and costs, and increased tool accu ....Ultrashort pulse laser for ultra-hard machine tools processing. This project aims to develop an advanced high-precision ultrashort pulse laser technique for shaping and sharpening cutting tools. It expects to generate new knowledge and new technology in machine tool fabrication using an innovative approach for processing ultra-hard materials. The expected outcome is progressive machining capabilities with higher throughput, significantly reduced production time and costs, and increased tool accuracy and life. This should provide significant economic and safety benefits for the advanced manufacturing industry, enabling production of high-performance products across cutting-edge industries including defence, aerospace, medical tools, automotive, and clean-energy technologies.Read moreRead less
Identifying technological trajectories using machine learning algorithms. This project aims to improve our understanding of why scientific knowledge progresses in certain directions and what causes it to grow faster or slower across fields. The project will create new neural-network machine-learning algorithms to scan patent and scientific article texts (specifications and claims) for natural language concepts. The results will potentially be used by patent offices to improve their own database ....Identifying technological trajectories using machine learning algorithms. This project aims to improve our understanding of why scientific knowledge progresses in certain directions and what causes it to grow faster or slower across fields. The project will create new neural-network machine-learning algorithms to scan patent and scientific article texts (specifications and claims) for natural language concepts. The results will potentially be used by patent offices to improve their own database search, by business analytics companies to reveal new technologies and potential collaborators, and by academic economists to understand how knowledge travels and accumulates.
Read moreRead less
Building a bridge into preschool in remote Northern Territory communities. The focus of this project is the engagement of remote Indigenous children and families in a culturally appropriate, evidence-based early childhood education and care program that provides an opportunity to close the gap between Indigenous and non-Indigenous school achievement.
Improving regional secondary students' learning and well-being. Given the academic under-performance and lower life opportunities of Australian regional and rural students compared to their metropolitan counterparts, this research has the potential to make a significant social, cultural and economic contribution to the community. This research will be useful in developing an evidence-based framework to guide policy and practice in implementing an effective systematic approach to regional educati ....Improving regional secondary students' learning and well-being. Given the academic under-performance and lower life opportunities of Australian regional and rural students compared to their metropolitan counterparts, this research has the potential to make a significant social, cultural and economic contribution to the community. This research will be useful in developing an evidence-based framework to guide policy and practice in implementing an effective systematic approach to regional education and, where appropriate, other contexts. The research's economic benefit centres on gains for individuals, local communities, and the nation in enhancing regional students' academic achievements, sense of well-being and aspirations; leading to more productive citizens.Read moreRead less
Realising the Potential of Australia’s High Capacity Students. This project aims to investigate factors that contribute to high capacity students failing to improve in literacy, numeracy and problem solving compared with their lower capacity peers. The project aims to focus on protective factors that might mitigate against this negative association between capacity and achievement. The study and method extends previous research the influence of evidence-based decisions by collaborative teacher t ....Realising the Potential of Australia’s High Capacity Students. This project aims to investigate factors that contribute to high capacity students failing to improve in literacy, numeracy and problem solving compared with their lower capacity peers. The project aims to focus on protective factors that might mitigate against this negative association between capacity and achievement. The study and method extends previous research the influence of evidence-based decisions by collaborative teacher teams on student achievement. In partnership with the Victorian Department of Education and Early Childhood Development, this project seeks to identify ways that will enable systems of education to realise the learning potential of all students.Read moreRead less
Building executive function in imaginary play. This project aims to develop a sustainable, play-based program to increase the executive functions of children in the year prior to school. Executive functions (EF) are cognitive processes that control an individual’s behaviour and cognition and include processes such as working memory, inhibitory control and attention. There is evidence that EF skills are critical to a successful transition to formal learning environments and future academic achiev ....Building executive function in imaginary play. This project aims to develop a sustainable, play-based program to increase the executive functions of children in the year prior to school. Executive functions (EF) are cognitive processes that control an individual’s behaviour and cognition and include processes such as working memory, inhibitory control and attention. There is evidence that EF skills are critical to a successful transition to formal learning environments and future academic achievement, and that they are amenable to early intervention. Improving children’s EF skills in the year prior to school could produce lasting benefits across the school years, particularly for more vulnerable children. This project intends to inform professional development programs in early childhood education.Read moreRead less
Cloud-data centres resource allocation under bursty conditions. Cloud-data centres resource allocation under bursty conditions. The project aims to design, implement, and integrate solutions to manage resources in cloud data centres (CDCs), especially when operating under bursty workload conditions. CDCs are expected to assure performance whilst optimising resource usage at a minimum cost, but efficiently providing resources with specific performance requirements can be difficult. This project i ....Cloud-data centres resource allocation under bursty conditions. Cloud-data centres resource allocation under bursty conditions. The project aims to design, implement, and integrate solutions to manage resources in cloud data centres (CDCs), especially when operating under bursty workload conditions. CDCs are expected to assure performance whilst optimising resource usage at a minimum cost, but efficiently providing resources with specific performance requirements can be difficult. This project intends to develop scalable solutions with industry approved software plug-ins. This is expected to affect both trustworthy information and communications technology (ICT) infrastructure (delivering more resilient CDCs) and economic sustainability (reducing CDC usage cost for both users and providers) of today’s computerised society.Read moreRead less