Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0561231
Funder
Australian Research Council
Funding Amount
$671,715.00
Summary
MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools acc ....MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools accessible through the Internet will enable researchers to archive, retrieve and exchange data and software; access distributed MR image databases and the latest MR image analysis tools; schedule analysis tasks on the grid compute engine, the outcomes of which will be visualized by the visualization workstations.Read moreRead less
eResearch in the Neurosciences: Building collaborations in Asia. The proposed Australasian collaboration on eResearch in Neuroscience will promote and maintain the good health of Australians by 'improving critical mass through collaboration and information sharing' through increased access to advanced imaging technology in Korea and analysis techniques in Japan. The collaboration will also promote frontier technologies for building and transforming Australian industries by developing a creative ....eResearch in the Neurosciences: Building collaborations in Asia. The proposed Australasian collaboration on eResearch in Neuroscience will promote and maintain the good health of Australians by 'improving critical mass through collaboration and information sharing' through increased access to advanced imaging technology in Korea and analysis techniques in Japan. The collaboration will also promote frontier technologies for building and transforming Australian industries by developing a creative and innovative research environment and enhancing Australian scientists' participation in breakthrough science. Great national benefit can be derived from international research collaboration, due to the contribution frontier technology can make to science and health. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101283
Funder
Australian Research Council
Funding Amount
$400,998.00
Summary
Data synthesis to quantitatively understand and improve vision systems. This project aims to build high-fidelity synthetic data, to understand how a machine vision system reacts to environmental factors and consequently improve the ability of the system to generalise in the real world. This project expects to generate new knowledge in the area of computer vision using innovative techniques of data synthesis, analysis, and domain adaptation. The expected outcomes include new scientific discoverie ....Data synthesis to quantitatively understand and improve vision systems. This project aims to build high-fidelity synthetic data, to understand how a machine vision system reacts to environmental factors and consequently improve the ability of the system to generalise in the real world. This project expects to generate new knowledge in the area of computer vision using innovative techniques of data synthesis, analysis, and domain adaptation. The expected outcomes include new scientific discoveries and domain adaptation algorithms derived from synthetic data for real-world applications. The benefits are expected to be widespread across sectors such as transportation, security, and manufacturing, including safer robotic navigation, defect detection, and smart video surveillance to improve community safety.Read moreRead less
Multiview Complete Space Learning for Sparse Camera Network Research. Data analytics in video surveillance and social computing is a problem because data are represented by multiple heterogeneous features. This project will develop a multiview complete space learning framework to exploit heterogeneous properties to represent images obtained from sparse camera networks. It will integrate multiple features to identify people and understand behaviour, to build a database of activities occurring in ....Multiview Complete Space Learning for Sparse Camera Network Research. Data analytics in video surveillance and social computing is a problem because data are represented by multiple heterogeneous features. This project will develop a multiview complete space learning framework to exploit heterogeneous properties to represent images obtained from sparse camera networks. It will integrate multiple features to identify people and understand behaviour, to build a database of activities occurring in a wide area of surveillance. It will expand frontier technologies and safeguard Australia by providing warnings for hazardous (for example, overcrowding, trespassing), criminal, and terrorist situations. Results will be applicable internationally and enhance Australia’s role in machine learning and computer vision communities.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
Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatm ....Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatments through the linking of relevant biochemical information. By delivering new methods that improve the compilation of knowledge about chemicals and drugs from textual information resources, the project hopes to enable faster drug discovery.Read moreRead less
High resolution single particle analysis of biological macromolecules. One of the great challenges of cell biology is to increase the rate of atomic resolution structure determination, particularly of membrane proteins and macromolecular assemblies. The current rate-limiting step is high quality crystal production. Our goal is to prove that protein structures can be determined to atomic resolution by single-particle analysis. 3D structures will be produced by computationally aligning high-resolu ....High resolution single particle analysis of biological macromolecules. One of the great challenges of cell biology is to increase the rate of atomic resolution structure determination, particularly of membrane proteins and macromolecular assemblies. The current rate-limiting step is high quality crystal production. Our goal is to prove that protein structures can be determined to atomic resolution by single-particle analysis. 3D structures will be produced by computationally aligning high-resolution electron microscope images of individual, randomly oriented molecules. The importance of this project is highlighted by the fact over 120,000 protein sequences are already databased, a number set to increase rapidly as new genome sequencing projects are completed.
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Investigation and development of robust rule discovery and classification system. This research focuses on a national research priority, namely smart information use. The expected outcomes of the project will greatly advance intelligent system design, such as automatic decision making, fault detection and problem diagnosis, for finance, medical, telecom and many other areas. It has great potential for commercialisation and earning incomes for the future research. The publications will benefit th ....Investigation and development of robust rule discovery and classification system. This research focuses on a national research priority, namely smart information use. The expected outcomes of the project will greatly advance intelligent system design, such as automatic decision making, fault detection and problem diagnosis, for finance, medical, telecom and many other areas. It has great potential for commercialisation and earning incomes for the future research. The publications will benefit the future development of intelligent systems for dealing with missing data. This project directly supports a PhD student and two research assistants who will most likely continue their higher degree study. These contribute to regional tertiary education.Read moreRead less
Increasing data quality with group associations in outsourcing environments. Outsourcing of data storage is increasingly common, but poses major problems for data utility and confidentiality. This project aims to discover how tuples (data structures) in fragments can be grouped to increase the utility of queries executed over fragments. The project will create a framework that satisfies information protection goals while achieving utility for queries. The developed algorithms and techniques will ....Increasing data quality with group associations in outsourcing environments. Outsourcing of data storage is increasingly common, but poses major problems for data utility and confidentiality. This project aims to discover how tuples (data structures) in fragments can be grouped to increase the utility of queries executed over fragments. The project will create a framework that satisfies information protection goals while achieving utility for queries. The developed algorithms and techniques will formally specify and develop a model to validate loose association rules while minimising data leakage risks. The outcomes will benefit Australians through enabling sharing and linking increasingly large datasets securely and cheaply.Read moreRead less
Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin ....Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.Read moreRead less