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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Vision performance in relationship to spectacle lens design. Refractive errors such as short-sightedness, long-sightedness or presbyopia (age related decline in near vision) are the leading causes of visual impairment in the world. Of these, presbyopia affects almost 100% of the population above 45 years of age. This represents over 40% of all Australians. Although spectacles provide a safe and easy means of correcting refractive errors, they affect quality of life due to distorted vision, disco ....Vision performance in relationship to spectacle lens design. Refractive errors such as short-sightedness, long-sightedness or presbyopia (age related decline in near vision) are the leading causes of visual impairment in the world. Of these, presbyopia affects almost 100% of the population above 45 years of age. This represents over 40% of all Australians. Although spectacles provide a safe and easy means of correcting refractive errors, they affect quality of life due to distorted vision, discomfort such as head and neck ache and cosmetic effects. The goals of the project are to better understand the visual performance of young and old people who wear glasses and to develop improved spectacle lens designs to provide clear and comfortable vision over a range of distances.Read moreRead less
Semantic change detection through large-scale learning. This project aims to develop technologies which understand the content of images before higher-level analysis is performed. This approach is intended to allow more accurate and reliable decisions to be made using automated image analysis than has previously been possible. The project will particularly investigate the detection of change in the contents of an image.
Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently ....Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently learn complex interaction and navigation behaviours that transfer to unseen environments. Our research should benefit new applications in domains of economic and societal importance that are currently too complex, unsafe, and uncertain for robot assistants, such as aged care, advanced manufacturing and domestic robotics.Read moreRead less
Early career teacher induction: Supporting precarious teachers. This project aims to investigate the ways in which Australian induction policies support precariously employed early career teachers to effectively manage student classroom behaviour. This project expects to generate new knowledge of workforce development and induction experiences of early career teachers employed on casual and short-term contracts. Expected outcomes of this project include alternative policy and practice recommenda ....Early career teacher induction: Supporting precarious teachers. This project aims to investigate the ways in which Australian induction policies support precariously employed early career teachers to effectively manage student classroom behaviour. This project expects to generate new knowledge of workforce development and induction experiences of early career teachers employed on casual and short-term contracts. Expected outcomes of this project include alternative policy and practice recommendations to support the transition of insecure replacement teachers within the profession. The benefits of this research include, improving teachers’ classroom management practices; the retention of new teachers; improving teacher workforce development; and building a healthier education system. Read moreRead less
Supporting teachers and teaching in flexible and non-traditional schools . This project aims to address a critical gap in knowledge about the experiences and conditions of people who teach in flexible and non-traditional schools in Australia. These schools provide a second chance at education for young people with challenging behaviours and/or learning problems. This project expects to generate new knowledge about the experiences and needs of these teachers, using a combination of in-depth resea ....Supporting teachers and teaching in flexible and non-traditional schools . This project aims to address a critical gap in knowledge about the experiences and conditions of people who teach in flexible and non-traditional schools in Australia. These schools provide a second chance at education for young people with challenging behaviours and/or learning problems. This project expects to generate new knowledge about the experiences and needs of these teachers, using a combination of in-depth research methods. Expected outcomes include detailed understanding of support needs for this workforce. This will significantly benefit teachers, sponsors and principals through recommendations on best practice management of this important work, along with evidence-based training artefacts for staff recruitment and retention.
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Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Pursuing equity in high poverty rural schools: improving learning through rich accountabilities. Poor performance of students in schools located in high poverty communities is a pressing educational problem for Australia, with educational disadvantage in poor rural communities in particular demanding amelioration. The evidence suggests the equity and quality of schooling outcomes are centrally important to the nation's economic future, the strength of Australian democracy, social inclusion and a ....Pursuing equity in high poverty rural schools: improving learning through rich accountabilities. Poor performance of students in schools located in high poverty communities is a pressing educational problem for Australia, with educational disadvantage in poor rural communities in particular demanding amelioration. The evidence suggests the equity and quality of schooling outcomes are centrally important to the nation's economic future, the strength of Australian democracy, social inclusion and a unified nation. In strengthening policy and practice knowledge about educative usage of performance data and the development of rich forms of accountability, the research will advance the academic literature and provide an evidence base for success of the national partnership on low socio-economic status schools.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
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