A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons fo ....A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons for rejection at construction sites, resulting in significant costs, waste, and delays. Multimodal data sources will be used to provide a reliable workability estimate in real time, enabling construction teams to identify and rectify workability issues in transit while continuously monitoring the adjustments effects.Read moreRead less
Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over ti ....Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over time and captured by different sensors and identify correlations between historic security incidents and current data attacks. This project will significantly help to secure data on cloud for organisations in Australia and benefit fast-growing security sensitive data hosting and applications on cloud.Read moreRead less
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysi ....Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysis a monumental task. This project will provide advanced tools to detect fake website reviews and a cybersecurity system prototype ready to be used by industry, making Australia a leader in this field and resulting in a safer internet environment for all.Read moreRead less
Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.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