Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100030
Funder
Australian Research Council
Funding Amount
$270,000.00
Summary
Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software ....Test-bed for Wide-Area Software Defined Networking Research. Test bed for wide-area software defined networking research: This project aims to develop a wide-area test bed, spanning ten organisations, for conducting research and experimentation in the emerging disruptive technology of Software Defined Networking (SDN). SDN is likely to bring long-term transformation to the networking industry, much like cloud computing did, by enabling dynamic virtualised elastic network services under software control. The test bed will empower Australian researchers in network technologies and dependent applications (for example, multimedia and security) to collaboratively develop and demonstrate novel ideas at scale. This is expected to benefit Australia by giving our researchers international recognition in this nascent area, and developing a national talent pool for local industry.Read moreRead less
An integrative and distributed data management and workflow framework for e-research in biomedical imaging. This project will develop new tools for neuroimaging research: (i) efficient distributed infrastructure and workflow capabilities and (ii) semantic tools using existing ontological frameworks and specific neuroimaging ontologies.
These new capabilities will significantly enhance the productivity of neuroimaging research.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100129
Funder
Australian Research Council
Funding Amount
$270,000.00
Summary
Internet of things testbed for creating a Smart City. The Internet of Things Testbed facility replicates the conditions of a city-wide distribution of sensors and data collection applications to model in real time the functioning urban sensing elements of a smart city, translating vast amounts of sensor data into meaningful information and ultimately action.
Congestion control of networks: a unified stochastic framework. Systems such as the internet, wireless networks and the power grid require efficient allocation of shared resources. This research will develop ways to reduce delays in the internet and allow for growth in the power grid, without requiring additional infrastructure.
Software debuggers for next generation heterogeneous supercomputers. Supercomputing underpins a wide range of areas of importance to the Australian economy; mining, agriculture, engineering and medical research to name a few. It is of critical importance that software solutions in these areas behave correctly. This project will develop software tools and techniques to help locate errors in such applications.
Creating a smart city through internet of things. This project will deliver smart new ways of urban monitoring using ubiquitous sensing and data analysis for city management and sustainability. It will deliver researcher training, global clientele for local technology and a platform for local industry growth.
Improved Businesss Decision-Making via Liquid Process Model Collections. This project aims to develop an innovative approach to create and update as necessary the large collection of business process models that represent a complex organisation, so that this collection captures the actual way in which the organisation performs its business processes. Deploying theoretical, conceptual and empirical research, this project aims to capitalise on the value hidden in large process data, as recorded in ....Improved Businesss Decision-Making via Liquid Process Model Collections. This project aims to develop an innovative approach to create and update as necessary the large collection of business process models that represent a complex organisation, so that this collection captures the actual way in which the organisation performs its business processes. Deploying theoretical, conceptual and empirical research, this project aims to capitalise on the value hidden in large process data, as recorded in event logs. The approach is intended to be implemented in an open-source technology to facilitate advanced investigations and predictions that can ultimately lead to better strategic decision-making. This technology also has the potential to become a research-enabling tool for the large research community in business process management.Read moreRead less
Cost-aware business process management. The project aims to inform business process management (BPM) with the latest insights from the field of management accounting in order to make BPM systems cost-aware. By incorporating the cost dimension, organisations can obtain an accurate and immediate overview of the true cost of their processes and make cost-informed decisions.
Discovery Early Career Researcher Award - Grant ID: DE170101134
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Feasible algorithms for big inference. This project aims to develop algorithms for computationally-intensive statistical tools to analyse Big Data. Big Data is ubiquitous in science, engineering, industry and finance, but needs special machine learning to conduct correct inferential analysis. Computational bottlenecks make many tried-and-true tools of statistical inference inadequate. This project will develop tools including false discovery rate control, heteroscedastic and robust regression an ....Feasible algorithms for big inference. This project aims to develop algorithms for computationally-intensive statistical tools to analyse Big Data. Big Data is ubiquitous in science, engineering, industry and finance, but needs special machine learning to conduct correct inferential analysis. Computational bottlenecks make many tried-and-true tools of statistical inference inadequate. This project will develop tools including false discovery rate control, heteroscedastic and robust regression and mixture models, via Big Data-appropriate optimisation and composite-likelihood estimation. It will make open, well-documented, and accessible software available for the scalable and distributable analysis of Big Data. The expected outcome is a suite of scalable algorithms to analyse Big Data.Read moreRead less
New play pedagogies for teaching and learning in the early years. Traditional play-based learning in early childhood education cannot account for new play: very young children's everyday play with technologies, digital media and popular culture. This project uses a recently developed web-mapping tool to create a pedagogical approach to new play. The pedagogical approach to new play comprises teaching practices and learning outcomes that capitalise on the educational potential of children's every ....New play pedagogies for teaching and learning in the early years. Traditional play-based learning in early childhood education cannot account for new play: very young children's everyday play with technologies, digital media and popular culture. This project uses a recently developed web-mapping tool to create a pedagogical approach to new play. The pedagogical approach to new play comprises teaching practices and learning outcomes that capitalise on the educational potential of children's everyday play with technologies, digital media and popular culture. It aims to enable teachers to work from a theorised and empirically validated perspective for connecting young children's everyday play with technologies, digital media and popular culture artefacts to their 21st century learning needs.Read moreRead less