Learning to talk whitefella way. Many Indigenous children speak Aboriginal English or 'Kriol', which often sounds very different to Standard Australian English. Understanding the differences between these languages, and how 'Kriol' affects the learning of English, will help us to better assist Indigenous children to learn English and likely improve their educational outcomes.
Discovering the developmental trajectory of lexical stress production. In English words some syllables are more strongly stressed than others. Most children will learn to emphasise these syllables appropriately but some will not. This project will help to understand the normal development of this vital aspect of speech production and allow more effective assistance to those who experience difficulties.
Functional imaging of colour pathways in the living eye. In order to repair or regenerate a diseased eye, we require knowledge of the normal pattern or nerve cell connections, and knowing how biology solves the problem of colour vision can be used to improve the design of artificial vision systems. The adaptive optics machine we will build in this project can be used to image nerve cells, fine blood vessels, and nerve fibre bundles in the normal and diseased eye. This will improve Australia's re ....Functional imaging of colour pathways in the living eye. In order to repair or regenerate a diseased eye, we require knowledge of the normal pattern or nerve cell connections, and knowing how biology solves the problem of colour vision can be used to improve the design of artificial vision systems. The adaptive optics machine we will build in this project can be used to image nerve cells, fine blood vessels, and nerve fibre bundles in the normal and diseased eye. This will improve Australia's research and development capacity in this new area of medical diagnostics. Our machine will be made available to other Australian laboratories and will improve the national capacity for making further scientific discoveries about how the visual system works.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less
Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of grea ....Methodologies for face recognition under varying imaging conditions. Face recognition systems are heavily dependent on the nature of the input to the system. Variability in appearance due to changes in illumination, expression, pose, etc. can reduce the recognition results of the existing systems. The aim of this project is to develop new techniques to improve the recognition accuracy in natural environment where unwanted image variations exist. The development of such techniques will be of great importance to Australia's security and safety. The outcome of this research will provide the first steps towards formulating the next generation recognition systems that will improve the suitability of the face recognition for use in security, surveillance, intelligent robotics, banking, and smart environments.Read moreRead less
Combating Fake News on Social Media: From Early Detection to Intervention. The project aims to detect fake news early to minimise the negative impact of false information. This project expects to devise novel solutions to address technical challenges for detection of fake news with scarce signals. Expected outcomes of this project include a suite of data mining and machine learning models for identification of fake news from the social media stream, prediction of user propagation of false infor ....Combating Fake News on Social Media: From Early Detection to Intervention. The project aims to detect fake news early to minimise the negative impact of false information. This project expects to devise novel solutions to address technical challenges for detection of fake news with scarce signals. Expected outcomes of this project include a suite of data mining and machine learning models for identification of fake news from the social media stream, prediction of user propagation of false information as well as recommendation of truthful news to counteract adversarial fake news. This project should generate technologies that enhance the integrity of the online echo system and benefit media providers and online population within Australia and across the world. Read moreRead less
Using written language to probe speech recognition models. Speech recognition models fall into two principal classes, with fundamentally different processing architectures. Feedback models (e.g. TRACE, McClelland & Elman, 1986) allow lexical knowledge to exert top-down control over phonemic analysis. Feedforward models (e.g. Merge, Norris, McQueen & Cutler, 2000) assume that information flow is entirely bottom-up. Our project adopts an innovative approach to testing between these model classe ....Using written language to probe speech recognition models. Speech recognition models fall into two principal classes, with fundamentally different processing architectures. Feedback models (e.g. TRACE, McClelland & Elman, 1986) allow lexical knowledge to exert top-down control over phonemic analysis. Feedforward models (e.g. Merge, Norris, McQueen & Cutler, 2000) assume that information flow is entirely bottom-up. Our project adopts an innovative approach to testing between these model classes, by examining the influence of written-word knowledge on speech perception. To distinguish the models, contrasts must test different processing levels and examine strategy effects. TRACE favors broad effects with limited strategic influence; Merge favors lexical effects that are necessarily sensitive to strategic factorsRead moreRead less
Reconciling perceptual and cognitive accounts of dyslexia: The neural rate deficit hypothesis. The proposed research will form part of a co-ordinated program to understand the causes of dyslexia, a disorder that affects a large number of children and often persists into adulthood. It complements parallel efforts to elucidate the genetic basis of dyslexia, the heterogeneity and subtypes of dyslexia, and the developmental precursors to the disorder. This research will inform early intervention and ....Reconciling perceptual and cognitive accounts of dyslexia: The neural rate deficit hypothesis. The proposed research will form part of a co-ordinated program to understand the causes of dyslexia, a disorder that affects a large number of children and often persists into adulthood. It complements parallel efforts to elucidate the genetic basis of dyslexia, the heterogeneity and subtypes of dyslexia, and the developmental precursors to the disorder. This research will inform early intervention and remediation efforts and will also assist in the understanding of the normal process of reading acquisition in children.Read moreRead less
Ultra-low fouling active surfaces. This project aims to develop chemistries and fabrication approaches through innovative materials evaluation to develop ultra-low fouling active electrode surfaces. Development of ultra-low fouling surfaces will have significant impact in a range of applications where system or device failure is attributed to fouling. The growing field of bionics, where implantable electronic devices interface directly with the nervous system, is one such device. The expected ou ....Ultra-low fouling active surfaces. This project aims to develop chemistries and fabrication approaches through innovative materials evaluation to develop ultra-low fouling active electrode surfaces. Development of ultra-low fouling surfaces will have significant impact in a range of applications where system or device failure is attributed to fouling. The growing field of bionics, where implantable electronic devices interface directly with the nervous system, is one such device. The expected outcomes will be an understanding of the material requirements that lead to the elimination of protein and cell accumulation at surfaces that degrades the performance and lifetime of these implants. The findings will benefit any application where fouling is a problem.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