Market segmentation methodology: attacking the 'Too Hard' basket. Businesses embrace market segmentation to identify and target clients. However, poor segmentation analysis leads to poor segment choice. This project will develop tools to improve segmentation analysis and will test the resulting tools in tourism, foster care and climate change mitigating behaviours, and produce usable, transferable recommendations.
Ageing and self-regulation. Australia is faced with an ageing population, and thus an increasingly important national goal is ageing well and ageing productively. Our preliminary research suggests that self-regulation may be a significant problem for older Australians. The proposed research will provide a clearer picture of when and why older adults have difficulties regulating their behaviour, and which older adults are particularly susceptible to lapses in self-control. If older adults do hav ....Ageing and self-regulation. Australia is faced with an ageing population, and thus an increasingly important national goal is ageing well and ageing productively. Our preliminary research suggests that self-regulation may be a significant problem for older Australians. The proposed research will provide a clearer picture of when and why older adults have difficulties regulating their behaviour, and which older adults are particularly susceptible to lapses in self-control. If older adults do have difficulties self-regulating, and if these self-regulation failures incur health, financial and social costs, by gaining a clearer understanding of this problem, the proposed research will take an important step in improving the lives of older Australians. Read moreRead less
Everyday cognition in older adulthood: Mechanisms contributing to the age-prospective memory paradox. Australia is faced with an ageing population, and thus an increasingly important goal is ageing well and ageing productively. The proposed research will clarify why older adults perform extremely well on prospective memory (PM) tasks based in everyday environments, but very poorly on PM tasks that take place in the controlled situation of the laboratory. Advancing our understanding of why this ....Everyday cognition in older adulthood: Mechanisms contributing to the age-prospective memory paradox. Australia is faced with an ageing population, and thus an increasingly important goal is ageing well and ageing productively. The proposed research will clarify why older adults perform extremely well on prospective memory (PM) tasks based in everyday environments, but very poorly on PM tasks that take place in the controlled situation of the laboratory. Advancing our understanding of why this 'paradoxical' pattern of age effects occurs will help clarify how other aspects of everyday cognition in older adulthood may be optimised, and consequently take an important step in improving the lives of older adults. The results will also inform development of rehabilitation strategies for clinical groups who present with PM difficulties. Read moreRead less
A process model of visual working memory. This project aims to develop a process model of encoding of items into memory. Working memory is central to almost all cognitive functions, but little is known about short-term memory for visual information. Progress in this area is slow because of a focus on models that do not specify the processes underlying memory, and no model explains the processes that would limit the number of items the memory can hold to four. A process model is expected to addre ....A process model of visual working memory. This project aims to develop a process model of encoding of items into memory. Working memory is central to almost all cognitive functions, but little is known about short-term memory for visual information. Progress in this area is slow because of a focus on models that do not specify the processes underlying memory, and no model explains the processes that would limit the number of items the memory can hold to four. A process model is expected to address fundamental issues in visual working memory.Read moreRead less
Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive ....Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive and specific detection of early cancers, the potential reductions in morbidity and mortality from breast cancer will be of immense value. Successful implementation of the proposed project will further enhance Australia's position as a world leader in biomedical research and application of computational technologies to health problems.Read moreRead less
Determining principles for successful episode retrieval of repeated events. This project aims to develop the first-ever set of explanatory principles for how people successfully retain and retrieve individual episode memories from repeated experiences (e.g., one occurrence of a routine social encounter or job-related activity). By deepening our understanding of how memory works, this new knowledge is expected to lay the foundation for interview guidance and ongoing research aimed at enhancing th ....Determining principles for successful episode retrieval of repeated events. This project aims to develop the first-ever set of explanatory principles for how people successfully retain and retrieve individual episode memories from repeated experiences (e.g., one occurrence of a routine social encounter or job-related activity). By deepening our understanding of how memory works, this new knowledge is expected to lay the foundation for interview guidance and ongoing research aimed at enhancing the proficiency of investigations into matters that rely on detailed and accurate accounts of specific episodes. This includes workplace or traffic accident investigations, infectious disease contact tracing, as well as prosecution of repeated sexual offences.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Taming the uncertainty in trajectory data. This project aims to develop effective and efficient methods to manage large scale uncertain trajectory data. It provides individuals, business, government and social groups the ability to explore significant uncertain trajectories and their patterns, for important usages in location based services, logistic, transportation and tourism.
Ageing, Inhibition, and Social Control - steps towards improving the lives of older adults. Australia is faced with an ageing population, and thus an increasingly important national goal is ageing well and ageing productively. The proposed research will extend our preliminary findings on ageing and social inappropriateness to provide a clearer picture of when and why this occurs, and among whom. The proposed research will also examine the mental and physical health consequences of social inappro ....Ageing, Inhibition, and Social Control - steps towards improving the lives of older adults. Australia is faced with an ageing population, and thus an increasingly important national goal is ageing well and ageing productively. The proposed research will extend our preliminary findings on ageing and social inappropriateness to provide a clearer picture of when and why this occurs, and among whom. The proposed research will also examine the mental and physical health consequences of social inappropriateness longitudinally. If cognitive losses do lead to social losses, with attendant negative health consequences, by gaining a clearer understanding of this problem, the proposed research will take an important step in improving the lives of older adults.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less