Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.Read moreRead less
A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword ....A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword search, subgraph isomorphism and substructure query techniques. This project is expected to significantly accelerate the application of new technologies, for example, big data analytics and Internet of Things, in many of Australia's critical domains such as e-Health, smart cities, and cybersecurity.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100153
Funder
Australian Research Council
Funding Amount
$361,446.00
Summary
Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to impr ....Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to improve project awareness, and to increase productivity goals. The outcomes would include a comprehensive decision and awareness support system for software projects, based on automating the creation and continual updating of developer activity summaries and measures.Read moreRead less
Determination Of Irradiation Dose Efficacy For Use In Impaction Grafting At Revision Joint Replacement
Funder
National Health and Medical Research Council
Funding Amount
$411,517.00
Summary
Primary hip replacement is a successful intervention for hip disease, but 10-15% of hip prostheses fail and require revision surgery within 10-15 years. At the time of revision, significant bone loss around the failed prosthesis is not uncommon. A bone reconstruction procedure, called impaction grafting, where donor bone is minced and placed in the areas of deficient bone before implanting the new prosthesis, has shown to give good results at more than ten years in some centres. A high incidence ....Primary hip replacement is a successful intervention for hip disease, but 10-15% of hip prostheses fail and require revision surgery within 10-15 years. At the time of revision, significant bone loss around the failed prosthesis is not uncommon. A bone reconstruction procedure, called impaction grafting, where donor bone is minced and placed in the areas of deficient bone before implanting the new prosthesis, has shown to give good results at more than ten years in some centres. A high incidence of early complications of this procedure have included loss of fixation within the bone. Fracture of the bone around prostheses has also reported in some centres. These events require more surgery, putting the patient at higher risk greater complications and longer rehabilitations. Recent improvements in surgical technique and donor bone preparation have improved results. A current debate questions whether the dose of irradiation can be reduced from 25 kGy, while maintaining sterility of allografts. The risk of bacterial contamination in allografts is low, and irradiation reduces the mechanical strength of the graft, contributing to complications when irradiated bone is used. The benefits of decontaminating the bone may be outweighed by the higher risk for failure due to poor bone quality and resulting prosthesis instability. We will use ISO standards to test the validity of radiation dose for sterilising bone ex vivo. In the absence of controlled human studies, our aim is also to compare the results of impaction grafting with non-irradiated bone versus bone irradiated at current doses used by Australian bone banks, and lower doses indicated by ex vivo testing. We will use a large animal model of revision hip replacement, with precise measures of prosthesis stability. The results of this study will guide clinical decisions regarding the efficacy of current bone graft preparation procedures and the use of irradiated bone in human hip replacement surgery.Read moreRead less
Fault detection and identification in nonlinear complex systems. Complex systems usually comprise a large number of inter-dependent subsystems linked together to perform a certain task. Examples of such systems are power systems, irrigation systems, air traffic control systems, to name a few. Such systems are subject to component failure or malfunction. Total failure can cause an unacceptable financial losses and/or danger to personnel. It is therefore extremely essential, from economic and safe ....Fault detection and identification in nonlinear complex systems. Complex systems usually comprise a large number of inter-dependent subsystems linked together to perform a certain task. Examples of such systems are power systems, irrigation systems, air traffic control systems, to name a few. Such systems are subject to component failure or malfunction. Total failure can cause an unacceptable financial losses and/or danger to personnel. It is therefore extremely essential, from economic and safety view points, that a way be found to ensure reliable and viable operation of complex plants. A first step in achieving this goal is to detect faults on-line and in real-time when they occur and identify their location and characteristics, which is the aim of this project.Read moreRead less
Special Research Initiatives - Grant ID: SR0354693
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
Australian e-Research Grid. The e-Research Grid program will research and implement core Grid technologies on APAC and partner's deployed HPC resources, to underpin a broad range of Australian research. The computer science CIs will form collaborative links with international programs, adapting developments to local circumstances. The applications-domain CIs will leverage those into their scientific simulations and databases, using grid integrative techniques and portals. Many CIs participate in ....Australian e-Research Grid. The e-Research Grid program will research and implement core Grid technologies on APAC and partner's deployed HPC resources, to underpin a broad range of Australian research. The computer science CIs will form collaborative links with international programs, adapting developments to local circumstances. The applications-domain CIs will leverage those into their scientific simulations and databases, using grid integrative techniques and portals. Many CIs participate in other RNs linking to their motivating applications, enhancing prospects for research and integration. They participate in the APAC Grid program, leveraging 75 HPC staff nationally. A key aim is interoperability with "real-world Grids": eg e-learning & e-health programs.Read moreRead less
Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those ....Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those people and vehicles are doing), industrial prototyping and inspection (measuring the size and shape of objects), urban planning (laser scanning streetscapes to create computer models of cities), entertainment industry (movie special effects and games), etc. Read moreRead less
Intelligent Technologies for Smart Cryptography. This project aims to improve cybersecurity by automating the process of generating cryptographic software for smart devices. The expected outcomes are tools that automatically produce efficient cryptographic software that resists attacks. The main benefit of this project is to reduce the amount of expert labour required when developing secure software.
Visual tracking with environmental constraints. By incorporating high level scene understanding into visual tracking, this project will improve the capacity to monitor and analyse complex patterns of activity in video. This has many applications in public safety and security, but the project will demonstrate it on the challenging task of tracking players during an Australian Football League (AFL) game to gather statistics on their performance.
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