Livable bathrooms for older people: designing out dependence in activities of daily living. This project aims to establish the design fundamentals needed for the development of more flexible, innovative and safer bathroom fixtures and domestic bathroom environments for older Australians. It provides an understanding of bathroom features and characteristics that function well for older persons and those that diminish their wellbeing.
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
Transfer Learning for Genome Analysis and Personalised Recommendation. This project aims to improve the accuracy, adaptability, and comprehensiveness of health characteristic predictions and provide personalised recommendations for healthcare service and disease prevention. The deliverables include uncertainty learning and multi-source transfer learning methodologies for predictions based on genome analysis that distils and transfers useful knowledge from multiple sources into an Australian geno ....Transfer Learning for Genome Analysis and Personalised Recommendation. This project aims to improve the accuracy, adaptability, and comprehensiveness of health characteristic predictions and provide personalised recommendations for healthcare service and disease prevention. The deliverables include uncertainty learning and multi-source transfer learning methodologies for predictions based on genome analysis that distils and transfers useful knowledge from multiple sources into an Australian genome analysis model. A federated cross-domain recommender system will be developed to profile individuals and generate personalised recommendations. The outcomes are expected to create a paradigm shift in learning-based prediction and personalised recommendations to support healthcare services in complex environments. Read moreRead less
Predictive analytics from at home telemonitoring of vital signs. Predictive analytics from at home telemonitoring of vital signs. This project aims to reduce unscheduled admissions to hospital, by developing statistical models of people’s health using longitudinal measurements of vital signs and questionnaires. Hospital costs are becoming unsustainable and will overwhelm state budgets within thirty years. Telehealth monitoring to manage chronic disease is becoming increasingly routine internatio ....Predictive analytics from at home telemonitoring of vital signs. Predictive analytics from at home telemonitoring of vital signs. This project aims to reduce unscheduled admissions to hospital, by developing statistical models of people’s health using longitudinal measurements of vital signs and questionnaires. Hospital costs are becoming unsustainable and will overwhelm state budgets within thirty years. Telehealth monitoring to manage chronic disease is becoming increasingly routine internationally and should reduce unnecessary hospital admissions and health service costs. To scale up telehealth services nationally, automated means of assessing changes in an individual health status are needed. This project’s automated risk assessment models are expected to identify exacerbations and orchestrate an optimal response from health services to reduce unscheduled admissions to hospital.Read moreRead less
A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driv ....A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driving models. The project will lead to two innovations: in theory design an attack detection and prevention ecosystem for autonomous driving and in application implement a safety analysis toolset for industry-scale autonomous systems.Read moreRead less
Practice-based Systematized Nomenclature of Medicine (SNOMED) concept learning for drug-disease precaution early detection and refinement. The outcome of the Systematized Nomenclature of Medicine (SNOMED) concept learning system will help mitigate the impact of Adverse Drug Events hence directly contribute to the National Research Priority promoting and maintaining good health. It will tailor SNOMED knowledge to different clinical settings and provide evidence-based preventative health care. Th ....Practice-based Systematized Nomenclature of Medicine (SNOMED) concept learning for drug-disease precaution early detection and refinement. The outcome of the Systematized Nomenclature of Medicine (SNOMED) concept learning system will help mitigate the impact of Adverse Drug Events hence directly contribute to the National Research Priority promoting and maintaining good health. It will tailor SNOMED knowledge to different clinical settings and provide evidence-based preventative health care. The enabling methodology from this project for building computerised cognitive learning systems will be a frontier technology to enhance smart information use in clinical decision support. It will also contribute to the development of knowledge-based systems. A network version of the developed system will assist doctors working in rural and remote areas with their clinical decision making and prescribing practice.Read moreRead less
Temporal and spatial Bayesian network modelling for improved fog forecasting. This project aims to improve the accuracy of fog forecasting by explicitly modelling the spatial and temporal uncertainties surrounding fog formation. It is expected weather forecast services will adopt our approach to improve their predictions of fog, which will in turn help transport companies save costs, cut emissions and improve safety.
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
Next generation Customer Relationship Management (CRM) framework through intelligence and relationships from multiple information sources. In the current competitive times, organisations need to improve their service delivery and customer care processes and provide customised service to customers. This project develops a Customer Relationship Management (CRM) framework that can extract intelligence and relationships from multiple data sources to improve customer management and satisfaction in pu ....Next generation Customer Relationship Management (CRM) framework through intelligence and relationships from multiple information sources. In the current competitive times, organisations need to improve their service delivery and customer care processes and provide customised service to customers. This project develops a Customer Relationship Management (CRM) framework that can extract intelligence and relationships from multiple data sources to improve customer management and satisfaction in public and private organisations.Read moreRead less
Managing knowledge in telehealth projects: creating better solutions and improving patient care. Telehealth is the use of information and communication technologies for the delivery of healthcare and medical education across a distance. This project will propose more effective ways to support telehealth initiatives by managing the knowledge and expertise that is an integral part of such projects, resulting in improved outcomes.