Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XM ....Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XML profiles for the different data sets and business processes, novel techniques for conjoint mining of structured and semi-structured data, and adaptive business intelligence techniques. The results will be validated using large real-world data sets provided by the partner organisation.Read moreRead less
Systems to Support Knowledge Creation in Learning Organisations. The proposed project will investigate the capacity of IT to support knowledge making for innovation in modern organisations. Prototypes of three flexible computer-based systems will be iteratively developed and evaluated for their support of knowledge workers in three different industries. The investigators are experienced in socio-technical approaches, which will be used to emphasise the integration between people and IT systems ....Systems to Support Knowledge Creation in Learning Organisations. The proposed project will investigate the capacity of IT to support knowledge making for innovation in modern organisations. Prototypes of three flexible computer-based systems will be iteratively developed and evaluated for their support of knowledge workers in three different industries. The investigators are experienced in socio-technical approaches, which will be used to emphasise the integration between people and IT systems. An interpretive study will determine how the systems can contribute to organisational learning, performance, and responsiveness to change. The outcomes will inform the designers of such systems and show Australian organisations how to gain competitive advantage by expanding their capacity to learn.Read moreRead less
Scenario driven management in a network environment. Scenario planning is the process of identifying plausible futures and their inherent risks. The organisation, the network within which it is embedded, and the environment in which the network operates, form a complex system of non-linear, dynamic, interrelationships. This project will develop a continuous process of scenario planning, capturing learning about the future as it emerges. The project fuses the use of agents for intelligent data co ....Scenario driven management in a network environment. Scenario planning is the process of identifying plausible futures and their inherent risks. The organisation, the network within which it is embedded, and the environment in which the network operates, form a complex system of non-linear, dynamic, interrelationships. This project will develop a continuous process of scenario planning, capturing learning about the future as it emerges. The project fuses the use of agents for intelligent data collection and negotiation with agent-based modelling to build powerful network-based scenario modelling systems for commercial applications. This outcome will place Australia on the frontier of smart information use.Read moreRead less
Intelligent Decision Support for Neonatal Analysis and Trend Detection. Nearly five percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the physiological data generated by the monitors is not extracted to provide an integrated picture of the baby's condition or to enable detection of trends and patterns in clinical a ....Intelligent Decision Support for Neonatal Analysis and Trend Detection. Nearly five percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the physiological data generated by the monitors is not extracted to provide an integrated picture of the baby's condition or to enable detection of trends and patterns in clinical and real-time physiological data. This project will develop a methodology and technology that supports neonatal analysis incorporating a framework to mine data for trend detection, resulting in higher survival rates.Read moreRead less
High Frequency Data Stream Event Correlation for Complex Neonatal Medical Alerts. Nearly twenty percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the data generated by these monitors is not integrated to enable the alerting of condition deterioration or early warning of possible condition onset. This project will d ....High Frequency Data Stream Event Correlation for Complex Neonatal Medical Alerts. Nearly twenty percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the data generated by these monitors is not integrated to enable the alerting of condition deterioration or early warning of possible condition onset. This project will develop a methodology and technology that supports the cross correlation of neonatal clinical and physiological data for complex neonatal medical alerts, through the use of agents within an event stream processor, resulting in higher survival rates.Read moreRead less
Generalizing Multi-level Decision Support Handling Multi-objectives, Multi-followers and Uncertainty for Critical Resource Planning. The proposed multi-level optimisation techniques and fuzzy multi-objective multi-follower multi-level decision support system can be used widely in government and industries of Australia to reduce decision blindness, improve decision effectiveness, and therefore has the potential to increase the competitiveness of organizations. Many organizations in Australia are ....Generalizing Multi-level Decision Support Handling Multi-objectives, Multi-followers and Uncertainty for Critical Resource Planning. The proposed multi-level optimisation techniques and fuzzy multi-objective multi-follower multi-level decision support system can be used widely in government and industries of Australia to reduce decision blindness, improve decision effectiveness, and therefore has the potential to increase the competitiveness of organizations. Many organizations in Australia are decentralized and have a hierarchical structure. The proposed techniques are extremely effective for such kinds of organizations in critical planning, management and policy making, including tourism resource planning, water resource management, financial planning, healthcare planning, land-use planning, production planning, transportation planning, and power market planning.Read moreRead less
Group Decision Support Systems for Fuzzy Multi-objective Decision Problems. Most real-world decisions in organisations are made by groups addressing multi-objectives. Further, the decision objectives are frequently characterized by fuzzy parameters and decision makers often utilise fuzzy judgments in attempting to reach optimal solutions. The project is the first to address all these issues: fuzzy objectives, fuzzy judgements, multi-objectives and groups in decision-making. The project will deve ....Group Decision Support Systems for Fuzzy Multi-objective Decision Problems. Most real-world decisions in organisations are made by groups addressing multi-objectives. Further, the decision objectives are frequently characterized by fuzzy parameters and decision makers often utilise fuzzy judgments in attempting to reach optimal solutions. The project is the first to address all these issues: fuzzy objectives, fuzzy judgements, multi-objectives and groups in decision-making. The project will develop a set of interactive decision-making methods to be used by groups solving fuzzy multi-objective decision problems with the allowance of fuzzy judgements, then develop a group decision support system to implement the methods. These outcomes can be immediately used by suitable Australian organisations.Read moreRead less
Analyzing and supporting cooperation management in online learning communities. Australian companies, universities and other organizations are competing with other nations in the ?knowledge market?, and given the size of Australia's population compared to many of its competitors, keeping a position at the forefront of knowledge production and innovation has become an economic necessity. Communities of practice and other forms of collaborative teams are becoming important as producers and dissemi ....Analyzing and supporting cooperation management in online learning communities. Australian companies, universities and other organizations are competing with other nations in the ?knowledge market?, and given the size of Australia's population compared to many of its competitors, keeping a position at the forefront of knowledge production and innovation has become an economic necessity. Communities of practice and other forms of collaborative teams are becoming important as producers and disseminators of knowledge and social capital. Our research will help such knowledge producing entities to make optimal use of modern communication media, employing elements of 'smart? technologies. Research outcomes will contribute to the design and support of knowledge building communities in form of guidelines and software tools.Read moreRead less
Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techn ....Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techniques but also deliever effective solutions to a number of real-life apllications.Read moreRead less
Prevention Of Complications In Type 2 Diabetes By Using ICT To Optimise Self-management
Funder
National Health and Medical Research Council
Funding Amount
$849,181.00
Summary
The impact of the diabetes epidemic on individuals and society is severe but can be reduced by improving diabetes self-management. Conducted in partnership with Diabetes Australia (Queensland, Victoria, WA) and Roche Diagnostics, this research will evaluate the 'real world' implementation of a telehealth program, already successfully trialled, which has the potential to provide a low cost and effective program to a large number of Australians with type 2 diabetes.