ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environme ....ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environments. EII will address 3 tightly coupled research themes: Ability to interoperate across existing heterogenous platforms & applications; Efficient processing of very large data sets; Technology adoption & impact. Generic results will be applicable to e-science and large business information systems installations.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
Special Research Initiatives - Grant ID: SR0354744
Funder
Australian Research Council
Funding Amount
$20,000.00
Summary
Improving Australia's Data Mining and Knowledge Discovery Research. The network will bring together over 50 active researchers in data mining and knowledge discovery to enhance and better coordinate Australia's impressive research performance in these dual disciplines. Specifically, the network will (a) facilitate communication and collaboration between researchers, (b) fund or underwrite opportunities for international collaboration, (c) run a number of specialist workshops and symposia and (d ....Improving Australia's Data Mining and Knowledge Discovery Research. The network will bring together over 50 active researchers in data mining and knowledge discovery to enhance and better coordinate Australia's impressive research performance in these dual disciplines. Specifically, the network will (a) facilitate communication and collaboration between researchers, (b) fund or underwrite opportunities for international collaboration, (c) run a number of specialist workshops and symposia and (d) establish a national annual conference.Read moreRead less