Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347194
Funder
Australian Research Council
Funding Amount
$411,000.00
Summary
Interactive Television Audience Research Laboratory. Interactive Television is a rapidly emerging platform for global media and e-commerce that is poised to dramatically transform the role of television in society. In collaboration with a range of university and industry partners, Murdoch University aims to establish Australia's first dedicated public research laboratory for assessing consumer motivation, evaluating program usability and theorising audience response to Interactive Television app ....Interactive Television Audience Research Laboratory. Interactive Television is a rapidly emerging platform for global media and e-commerce that is poised to dramatically transform the role of television in society. In collaboration with a range of university and industry partners, Murdoch University aims to establish Australia's first dedicated public research laboratory for assessing consumer motivation, evaluating program usability and theorising audience response to Interactive Television applications. The laboratory will feature specialised testing equipment designed to emulate real-world digital broadcasting environments, enabling rich data on viewing behaviour to be collected and analysed. As an independent facility, the laboratory will provide an invaluable resource for academic and industry research.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170101081
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis t ....Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis to efficiently and precisely analyse large-scale programs according to clients’ needs, thereby allowing compilers to generate safe, reliable and secure code. This project is expected to advance value-flow analysis for industrial-sized software, improve software reliability and security, and benefit Australian software systems and industries.Read moreRead less
Enhancing the content and experience of Interactive Childrens Television. Interactive television (iTV) as a participatory, on-demand communication provides a unique opportunity to significantly engage, entertain and educate preschool children. Through considerable industry partner collaboration and participation, this project will evaluate three distinct interactive options produced from selected children's television programs with proven success in Australia. Usability studies employing a vari ....Enhancing the content and experience of Interactive Childrens Television. Interactive television (iTV) as a participatory, on-demand communication provides a unique opportunity to significantly engage, entertain and educate preschool children. Through considerable industry partner collaboration and participation, this project will evaluate three distinct interactive options produced from selected children's television programs with proven success in Australia. Usability studies employing a variety of surveillance techniques will evaluate content design and user response. Children's viewing habits will be evaluated within a social context (the home) and a mobile lab setting using qualitative and quantitative assessment. The results will identify effective ways to produce meaningful interactivity and will encourage future industry based research.Read moreRead less
Special Research Initiatives - Grant ID: SR0354753
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
MESH: amalgamating innovative teams of cross-disciplinary collaborators for creativity in Media-arts, E-culture, Science and Humanities. MESH is a cross-disciplinary network that amalgamates a national array of sub-networks of research in digital arts, ICT and cross-cultural and policy negotiation. It boosts Australia's existing cross-disiciplinary strengths in Media-arts, E-culture, Science and Humanities by encouraging existing digital sub-networks to grow together via well-brokered communic ....MESH: amalgamating innovative teams of cross-disciplinary collaborators for creativity in Media-arts, E-culture, Science and Humanities. MESH is a cross-disciplinary network that amalgamates a national array of sub-networks of research in digital arts, ICT and cross-cultural and policy negotiation. It boosts Australia's existing cross-disiciplinary strengths in Media-arts, E-culture, Science and Humanities by encouraging existing digital sub-networks to grow together via well-brokered communications and demonstrations online and on-location. Progressively, MESH participants will discover existing harmonies whilst also inventing new languages and protocols leading to breakthroughs in cross-disciplinary collaboration and innovation. MESH encourages a 'paradigm shift' in digital research, realising the extraordinary potential that is ready but latent across Australia's arts and sciences.Read moreRead less
A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons fo ....A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons for rejection at construction sites, resulting in significant costs, waste, and delays. Multimodal data sources will be used to provide a reliable workability estimate in real time, enabling construction teams to identify and rectify workability issues in transit while continuously monitoring the adjustments effects.Read moreRead less