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
Special Research Initiatives - Grant ID: SR0567658
Funder
Australian Research Council
Funding Amount
$100,000.00
Summary
A cross-disciplinary collaboration to develop a national system for real-time detection of Adverse Drug Reactions using linked Australian health data. Our aim is to use existing administrative health data in the evidence-based, cost-effective and privacy-respecting discovery of Adverse Drug Reactions. This research is of vital importance, since adverse reactions to medicines currently represent one of the leading causes of hospitalisation and death in Australia. In a groundbreaking collaboration ....A cross-disciplinary collaboration to develop a national system for real-time detection of Adverse Drug Reactions using linked Australian health data. Our aim is to use existing administrative health data in the evidence-based, cost-effective and privacy-respecting discovery of Adverse Drug Reactions. This research is of vital importance, since adverse reactions to medicines currently represent one of the leading causes of hospitalisation and death in Australia. In a groundbreaking collaboration, we have successfully shown that large linked, administrative data sets are sufficiently rich to enable discovery of adverse drug reactions, but our analytic tools are at an early developmental stage. The outcome of this project would be innovative, effective and sustainable analytic tools for the discovery of unexpected associations between drugs and medical events.Read moreRead less
Information systems theory for location-based educational services in informal learning environments. Creating technology enhanced learning experiences will be critical to the way we educate and engage with future generations. This project will seek to develop a stronger theoretical basis for understanding how location-based technologies can enhance learning outcomes of school students visiting three of Australia's leading cultural institutions.
Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.Read moreRead less
Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human expl ....Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human explicit and implicit interest domains. The expected results of this application will not only maintain Australia's leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as cyber security, healthcare, and e-Commerce.Read moreRead less
Adaptive data stream processing in heterogeneous distributed computing environments using real-time context. This project falls within the ARC research priority goal, Smart Information Use. The innovative contributions of this project through the development of adaptive data stream mining algorithms for heterogeneous devices will have an impact on a range of emerging application areas such as:
1. Meeting time-critical, intelligent information needs of the mobile workforce (e.g. mobile healthca ....Adaptive data stream processing in heterogeneous distributed computing environments using real-time context. This project falls within the ARC research priority goal, Smart Information Use. The innovative contributions of this project through the development of adaptive data stream mining algorithms for heterogeneous devices will have an impact on a range of emerging application areas such as:
1. Meeting time-critical, intelligent information needs of the mobile workforce (e.g. mobile healthcare professionals, stockbrokers). 2. Improving Intelligent Transportation Systems via in-vehicle analysis and crash prevention. 3. Facilitating 'on-board' analysis in sensors that monitor the environment and patients. The project will enhance Australia's leading international role in the area of data stream processing in distributed computing environments.Read moreRead less
Floor trading versus computer trading - Does it matter? Computer systems for securities trading date from the 1980s. These systems are large, costly and extremely complex. Outcomes from their introduction were unforeseen and the relevant research literature is sparse. This project will investigate experimentally with a simulated trading system the effects on trading behaviour of important system parameters. Intelligent support systems for traders will also be developed and tested. The project ....Floor trading versus computer trading - Does it matter? Computer systems for securities trading date from the 1980s. These systems are large, costly and extremely complex. Outcomes from their introduction were unforeseen and the relevant research literature is sparse. This project will investigate experimentally with a simulated trading system the effects on trading behaviour of important system parameters. Intelligent support systems for traders will also be developed and tested. The project team combines needed expertise from the areas of human decision making, finance, and advanced information technologies. Results will be important for theory of market microstructure and interactive intelligent systems and also for an important industry in Australia.Read moreRead less
Context-aware mobile decision support systems for medical emergency management in mass gatherings. This project contributes to gaining a clearer understanding of the nature and requirements of medical emergency during mass gathering events. We will build and test a mobile real time decision support tool for improving efficiency of medical decisions to strengthen Australia's ability to manage potential health- related hazards. This project addresses research priorities of promoting and maintainin ....Context-aware mobile decision support systems for medical emergency management in mass gatherings. This project contributes to gaining a clearer understanding of the nature and requirements of medical emergency during mass gathering events. We will build and test a mobile real time decision support tool for improving efficiency of medical decisions to strengthen Australia's ability to manage potential health- related hazards. This project addresses research priorities of promoting and maintaining good health. It capitalizes on smart information use and will be of great benefit to mass gatherings emergency management. This project will also train highly qualified IT specialists critical to Australia's scientific and industrial development, thus increasing our competitiveness in information technology R&D. Read moreRead less
Learned Academies Special Projects - Grant ID: LA170100025
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social med ....Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social media archives or financial records in ways that will shed new light on many complex research questions. This project will map existing capability and infrastructure within and across disciplines, identify common and discipline-specific practices, challenges and opportunities, and assess technology, infrastructure, training and collaboration priorities for Australia.
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