Phonological effects on the development of inflectional morphology. This project investigates the mechanisms underlying typically developing children's variable omission of inflectional morphemes (for example, plural, past tense). The results will have significant implications for the evaluation and design of interventions for language-delayed populations where serious problems of communication persist.
Online Learning for Large Scale Structured Data in Complex Situations. Online Learning (OL) is the process of predicting answers for a sequence of questions. OL has enjoyed much attention in recent years due to its natural ability of processing large scale non-structured data and adapting to a changing environment. However, OL has three weaknesses: it does not scale for structured data; it often assumes that all of the data are equally important; it often considers that all of the data are compl ....Online Learning for Large Scale Structured Data in Complex Situations. Online Learning (OL) is the process of predicting answers for a sequence of questions. OL has enjoyed much attention in recent years due to its natural ability of processing large scale non-structured data and adapting to a changing environment. However, OL has three weaknesses: it does not scale for structured data; it often assumes that all of the data are equally important; it often considers that all of the data are complete and noise-free. These weaknesses limit its utility, because real data such as those that must be analysed in processing social networks, fraud detection do not satisfy the restrictions. The aim of this project is to develop theoretical and practical advances in OL that overcome the existing weaknesses.Read moreRead less
Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the bui ....Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the building of next generation of computer vision systems to work in open and dynamic environments. This should be able to produce solid benefits to the science, society, and economy of Australian via the application of these advanced intelligent systems.Read moreRead less
Square Eyes or All Lies? Understanding Children's Exposure to Screens. This project will examine Australian parents’ number one concern about their children’s health and behaviour – their interactions with electronic screens. Current screen time guidelines are based on low-quality evidence and lack the nuance required to address this complex issue. This project will use innovative technology to resolve these weaknesses. Wearable cameras will measure what children are doing on screens, and where, ....Square Eyes or All Lies? Understanding Children's Exposure to Screens. This project will examine Australian parents’ number one concern about their children’s health and behaviour – their interactions with electronic screens. Current screen time guidelines are based on low-quality evidence and lack the nuance required to address this complex issue. This project will use innovative technology to resolve these weaknesses. Wearable cameras will measure what children are doing on screens, and where, when, and how long they are doing it. The project will also investigate how screen time impacts children’s development and how it is influenced by their environment. This evidence will benefit children by improving screen time guidelines, and help parents understand the impact of screen time on children’s development.
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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
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less
Skin penetration of nanoparticles promoted by particle design, formulation and application method. This project seeks to better define the determinants of nanoparticle skin penetration and subsequent disposition in the body. The data would be used to guide minimal skin penetration of 'undesirable' nanoparticles and the properties required of 'safe' nanoparticles to enable effective human skin delivery in cosmetic and dermatological products.
How do protein quality control mechanisms maintain neuronal ageing? This project aims to interrogate how mechanisms of protein quality control act in the brain - an organ that is particularly vulnerable to a high load of misfolded protein - to maintain normal physiology during ageing. This project expects to make advances in cellular biochemistry and neuroscience, using an innovative proximity labelling approach to identify quality control regulators in neurons that specifically engage with misf ....How do protein quality control mechanisms maintain neuronal ageing? This project aims to interrogate how mechanisms of protein quality control act in the brain - an organ that is particularly vulnerable to a high load of misfolded protein - to maintain normal physiology during ageing. This project expects to make advances in cellular biochemistry and neuroscience, using an innovative proximity labelling approach to identify quality control regulators in neurons that specifically engage with misfolded proteins during ageing, within the nervous system of a living animal. Expected outcomes of this project will generate new knowledge of brain physiology and ageing relevant to all animals. This should provide significant benefits, such as a greater understanding of long-term brain functions including memory.Read moreRead less
Nanoscale silicon field-effect transistor diagnostic technology. This project aims to overcome barriers to the implementation of silicon field-effect transistor biosensors. It will investigate the biosensors’ physical and structural properties. This knowledge, combined with technological and conceptual advances, could foster the development of an advanced and translational point-of-care diagnostic technology to rapidly and sensitively detect malignant tissues. Such technology would have commerci ....Nanoscale silicon field-effect transistor diagnostic technology. This project aims to overcome barriers to the implementation of silicon field-effect transistor biosensors. It will investigate the biosensors’ physical and structural properties. This knowledge, combined with technological and conceptual advances, could foster the development of an advanced and translational point-of-care diagnostic technology to rapidly and sensitively detect malignant tissues. Such technology would have commercial potential and important societal benefits.Read moreRead less
The basis of recognition and disposal of dysfunctional proteins by clusterin. When proteins become damaged they can precipitate. A blood protein called clusterin prevents precipitation of damaged proteins. Clusterin does this by forming complexes with the damaged proteins. Clusterin is the first blood protein known to do this. We will discover which parts of clusterin are responsible for this activity. We will also discover whether cells can take up and dispose of the complexes of clusterin and ....The basis of recognition and disposal of dysfunctional proteins by clusterin. When proteins become damaged they can precipitate. A blood protein called clusterin prevents precipitation of damaged proteins. Clusterin does this by forming complexes with the damaged proteins. Clusterin is the first blood protein known to do this. We will discover which parts of clusterin are responsible for this activity. We will also discover whether cells can take up and dispose of the complexes of clusterin and damaged proteins. This work is important because some diseases (eg, Alzheimers disease) involve the toxic effects of abnormal protein precipitation. Understanding how clusterin works may help in developing better treatments for these diseases.Read moreRead less