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
Virtual Galleries: new media technologies to influence livelihood and arts participation in remote communities of the Northern Territory, Australia. The Virtual Galleries project addresses the issue of limited economic development in remote communities by introducing a user-controlled webcam and interactive 3-D (three-dimensional) Art Galleries into remote art centres to help people in remote communities to secure an income and create wealth and social wellbeing for themselves, their families an ....Virtual Galleries: new media technologies to influence livelihood and arts participation in remote communities of the Northern Territory, Australia. The Virtual Galleries project addresses the issue of limited economic development in remote communities by introducing a user-controlled webcam and interactive 3-D (three-dimensional) Art Galleries into remote art centres to help people in remote communities to secure an income and create wealth and social wellbeing for themselves, their families and their communities.Read moreRead less
ARC Centre of Excellence for Particle Physics at the Tera-Scale. The Large Hadron Collider, a gigantic particle accelerator at the CERN laboratory in Europe, has commenced operation. It will discover how particles gain mass, explore the identity of cosmological dark matter, and search for the new laws of physics needed for a satisfactory theory of the structure of matter. the Centre will provide the enhanced capability and institutional coordination and development needed for Australia to make a ....ARC Centre of Excellence for Particle Physics at the Tera-Scale. The Large Hadron Collider, a gigantic particle accelerator at the CERN laboratory in Europe, has commenced operation. It will discover how particles gain mass, explore the identity of cosmological dark matter, and search for the new laws of physics needed for a satisfactory theory of the structure of matter. the Centre will provide the enhanced capability and institutional coordination and development needed for Australia to make a major contribution to this most prestigious international project. It will transform Australia's standing in fundamental physics, provide unsurpassed training, generate many linkages in science and technology, and lead an important public outreach program.Read moreRead less
Interacting with visualisations of extremely large graph structures on large displays. The latest technological progressions have delivered very large data sets that can be modelled as graphs or networks. Examples include: social networks, biological data, and software structures. This project will develop techniques to allow users to visualise the graphs in the entirety and directly interact with data.
Construction of near optimal oscillatory regimes in singularly perturbed control systems via solutions of Hamilton-Jacobi-Bellman inequalities. Problems of optimal control of systems evolving in multiple time scales arise in a great variety of applications (from diet to environmental modelling). This project addresses the challenge of analytically and numerically constructing rapidly oscillating controls that would 'near optimally coordinate' the slow and fast dynamics.
Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, i ....Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, integer models usually assume the data is known with certainty, which is often not the case in the real world. This project will develop new theory and algorithms to enhance the analysis of integer models, including those that incorporating uncertainty, while also enabling the use of parallel computing paradigms. Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Information Seeking & Research Adoption: Assessing Communication Strategies. This project aims to determine the best ways to communicate wine research and to design tools to support research adoption. Adoption of research relies on effective use of information and technology by employees. Research into employees’ information practices in the workplace has been conducted in health care, education and other areas; however, the wine industry’s use of information and technology for adoption is unexp ....Information Seeking & Research Adoption: Assessing Communication Strategies. This project aims to determine the best ways to communicate wine research and to design tools to support research adoption. Adoption of research relies on effective use of information and technology by employees. Research into employees’ information practices in the workplace has been conducted in health care, education and other areas; however, the wine industry’s use of information and technology for adoption is unexplored. The project plans to assess the strategies used to share research with winemakers and grape growers (e.g. seminars, websites, social media), from information behaviour or web useability perspectives, to ensure industry needs are met appropriately. This research aims to have a direct and immediate impact on the wine industry. In addition to the immediate impact of new research innovations that will be implemented by our partner wine companies, the project will also change industry-wide approaches to extension. The partner organisations use extension strategies to showcase new innovations and our research will assess these organisations’ current practices, providing evidence to shape the design of future activities in Australia.Read moreRead less
How is information organised in the mind? Learning structured mental representations from data. One of the biggest questions in psychology is to understand the principles that the mind uses to organise information. This project is both a search for these underlying psychological laws, and an attempt to develop new statistical technologies and mathematical tools that can be used to organise information in applied settings.
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less