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SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the infor ....SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the information and contracts needed by IoT applications to discover, integrate, pay, and use sensors provided by another parties. These IoT advancements will provide significant economic, environmental, and social benefits via making low-cost and immediate sensing available across the world.Read moreRead less
A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medi ....A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medicine, which recognises that there are important differences between individuals with a particular disease, and that when patients are separated into sub-populations with similar disease patterns, treatment can be tailored to these sub-populations.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100292
Funder
Australian Research Council
Funding Amount
$285,000.00
Summary
Towards a stronger proof system for combinatorial optimisation. Combinatorial optimisation problems such as staff rostering, vehicle routing or resource allocation are central to the efficiency of many businesses and industries. This project will improve optimisation technology by using the low-level structure of the problems to find better solutions. This will save time, money and reduce environmental impact.
Livable bathrooms for older people: designing out dependence in activities of daily living. This project aims to establish the design fundamentals needed for the development of more flexible, innovative and safer bathroom fixtures and domestic bathroom environments for older Australians. It provides an understanding of bathroom features and characteristics that function well for older persons and those that diminish their wellbeing.
Information Systems (IS)-Impact utility and intuitiveness: a rigorous approach to relevance. This study aims to evaluate the key elements of models used in design science to assess the impact of information systems. The work will examine the extent to which rigour and relevance are incorporated into these models.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE140100061
Funder
Australian Research Council
Funding Amount
$1,000,000.00
Summary
FlashLite: A High Performance Machine for Data Intensive Science. FlashLite: a high performance machine for data intensive science: The 21st century has been described as the century of data. Experts predict an exponential growth in the amount of data that will be captured, generated and archived. Australia has made significant progress towards addressing some of the opportunities and infrastructure challenges posed by such rapid increase in data volumes. However, these investments do not addre ....FlashLite: A High Performance Machine for Data Intensive Science. FlashLite: a high performance machine for data intensive science: The 21st century has been described as the century of data. Experts predict an exponential growth in the amount of data that will be captured, generated and archived. Australia has made significant progress towards addressing some of the opportunities and infrastructure challenges posed by such rapid increase in data volumes. However, these investments do not address the growing need to process data. Conventional supercomputers are unable to meet the challenges of the data explosion. The large gap in latency and bandwidth between the processor, memory and disk subsystems means that the processor is often idle waiting to fetch data. This project will build a platform focussed on data intensive science.Read moreRead less
Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than ai ....Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than aiming to achieve invariance to it. The project will also research new data agnostic feature compaction capabilities to enable scalable learning on the world’s largest and challenging expression dataset available to us through international collaboration. Tackling these two major open problems will make accurate coding of facial expressions in natural environments achievable.Read moreRead less
Process algebra approach to distributed quantum computation and secure quantum communication. This project will develop effective methods for reasoning about the behaviours of distributed quantum computing and communicating systems. The developed methods will provide effective techniques for verifying security of quantum cryptographic protocols.
Omniscient face recognition for uncooperative subjects. The outcomes of this project will enable effective video surveillance technology to be developed for use by law enforcement and national security agencies. It will lead to reliable identification of humans at a distance by automatically detecting and recognising faces, for use in counter-terrorism surveillance and commercial robot-human interfaces.
Discovery Early Career Researcher Award - Grant ID: DE120100776
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Designing process models to support communication and decision-making. This project will develop guidelines to assist analysts in describing business processes by identifying theoretical factors of process model quality. The outcomes will make it easier to make informed decisions about process re-design, business innovation or software development, thus contributing to project cost savings and better processes.