Testing trade mark law's image of the consumer. An effective trade mark law is vital both to protect consumers and to allow businesses to build brand recognition. This project seeks to put Australian trade mark law on a firmer empirical footing by bringing together experts from psychology, law and marketing to test the law’s assumptions against actual consumer responses.
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
Data Enhancement, Integration and Access Services for Smarter, Collaborative and Adaptive Whole-of Water Cycle Management. The project provides a valuable opportunity to make significant impact on water resource management and create community partnerships that will go well beyond the lifetime of the project. The project is expected to contribute to improved water quality and healthier ecosystems. In turn, the scientifically rich research environment will benefit all involved. It will demonstrat ....Data Enhancement, Integration and Access Services for Smarter, Collaborative and Adaptive Whole-of Water Cycle Management. The project provides a valuable opportunity to make significant impact on water resource management and create community partnerships that will go well beyond the lifetime of the project. The project is expected to contribute to improved water quality and healthier ecosystems. In turn, the scientifically rich research environment will benefit all involved. It will demonstrate the capability of the Australian researchers in addressing complex problems in data integration and quality. In particular there will be far reaching benefits of research training for associated PhD students and staff.Read moreRead less
Minimising the inappropriate and unnecessary hospital admissions of frail older people. The health system will continue to experience massive pressures in both fiscal and human resource terms. Older patients present with multiple, complex conditions and tend to be admitted because clinicians often do not have the time to explore other options. This project will develop and evaluate a unique and robust model for minimising inappropriate hospital admissions through rapid assessment of suitability ....Minimising the inappropriate and unnecessary hospital admissions of frail older people. The health system will continue to experience massive pressures in both fiscal and human resource terms. Older patients present with multiple, complex conditions and tend to be admitted because clinicians often do not have the time to explore other options. This project will develop and evaluate a unique and robust model for minimising inappropriate hospital admissions through rapid assessment of suitability for home care and complete referral information for safety and quality. 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