Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the effici ....Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the efficiency and accuracy of product tracking in distribution networks. This project will place Australia at the forefront of RFID research. It will also be an excellent vehicle for educating young researchers and engineers in Australia.Read moreRead less
Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective. This project brings together experts in the fields of data mining and cognitive neuroscience. This project aims to develop new data analytics tools, algorithms, and models to combine complex multi-source neuroimage brain data and non-imaging data, to explore the interplays among these different data structures and identify novel functional patterns from complex brain graph structures. The research undertaken in this project ....Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective. This project brings together experts in the fields of data mining and cognitive neuroscience. This project aims to develop new data analytics tools, algorithms, and models to combine complex multi-source neuroimage brain data and non-imaging data, to explore the interplays among these different data structures and identify novel functional patterns from complex brain graph structures. The research undertaken in this project expects to provide practical data analysis approaches and establish the theoretical foundations for data mining with multiple sources of brain data.Read moreRead less
Effective, efficient and scalable processing of the graph of graphs. This project aims to develop novel approaches to realise the value of the graph of graphs (GoG), which has been widely used to capture the relations among the structured entities. Several key challenges will be addressed: better models to capture the similarity and cohesiveness of the structured entities, increased efficiency, and greater scalability of the processing and analytics of the GoG. The novel models and algorithms de ....Effective, efficient and scalable processing of the graph of graphs. This project aims to develop novel approaches to realise the value of the graph of graphs (GoG), which has been widely used to capture the relations among the structured entities. Several key challenges will be addressed: better models to capture the similarity and cohesiveness of the structured entities, increased efficiency, and greater scalability of the processing and analytics of the GoG. The novel models and algorithms developed within this project will be incorporated into a prototype for both evaluation and to demonstrate real-world practical value for business, industry, and academia. Success in this project should see significant benefits for many important applications such as health, cyber-security and e-commerce.Read moreRead less