Next generation data mining techniques for analysing large evolving networks. In order to understand complex systems such as the Internet or gene interactions, we need to analyse how the networks in these systems function and evolve. This project will provide new methods for extracting knowledge from large network databases so that scientists can learn about the operation of these complex systems.
Multi source inference from heterogeneous dynamic networks. Sophisticated big data applications in engineering, the social sciences and biology are now generating flows of data across multiple sources possessing a variety of structures. An emerging challenge is how to develop data mining methods that can cope with this complexity and diversity to make inferences and provide practical insights. This project will develop methods in tensor data mining that provide a new foundation for extracting us ....Multi source inference from heterogeneous dynamic networks. Sophisticated big data applications in engineering, the social sciences and biology are now generating flows of data across multiple sources possessing a variety of structures. An emerging challenge is how to develop data mining methods that can cope with this complexity and diversity to make inferences and provide practical insights. This project will develop methods in tensor data mining that provide a new foundation for extracting useful knowledge from multi source heterogeneous data sets. This will help accelerate discoveries in the next generation of data driven science.Read moreRead less
Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The succe ....Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The success of the project will directly contribute to the scientific foundation of Big Data computation. It will also contribute to the development of local industry involving cybersecurity, social media based recommendation, network management, and E-business.Read moreRead less
Added depth: automated high level image interpretation. Humans are very good at understanding the world through imagery, but computers lack this fundamental capacity because they lack experience of what they might see. This project will provide this experience by combining the large volumes of imagery on the Internet with three dimensional information generated by humans for other purposes.
Novel conversion process for carbon dioxide to chemicals. This project aims to develop a novel sorption enhanced material and system to convert atmospheric carbon dioxide (CO2) to methanol. Climate change is one of the primary long-term problems confronting humankind today. Since the production of CO2 through burning fossil fuel is far greater than the current usage of CO2, there is currently little alternative to storage. As a result, there is concerted effort globally to develop alternate use ....Novel conversion process for carbon dioxide to chemicals. This project aims to develop a novel sorption enhanced material and system to convert atmospheric carbon dioxide (CO2) to methanol. Climate change is one of the primary long-term problems confronting humankind today. Since the production of CO2 through burning fossil fuel is far greater than the current usage of CO2, there is currently little alternative to storage. As a result, there is concerted effort globally to develop alternate uses and conversion technologies for CO2. This project will help further this goal.Read moreRead less
Lightweight security solutions for wearable healthcare sensor devices. The aim of this project is to develop new methods to secure the data and context associated with body-wearable health monitoring devices. The novelty of the scheme is in making the methods work on resource-poor devices, by combining new security capabilities derived from the operating environment with conventional cryptographic techniques. This project aims to increase the trust that medical practitioners and insurance provid ....Lightweight security solutions for wearable healthcare sensor devices. The aim of this project is to develop new methods to secure the data and context associated with body-wearable health monitoring devices. The novelty of the scheme is in making the methods work on resource-poor devices, by combining new security capabilities derived from the operating environment with conventional cryptographic techniques. This project aims to increase the trust that medical practitioners and insurance providers can place on health data from wearable devices, and showcase Australian innovation in developing world-class security solutions. The outcome of this project is expected to be the development and demonstration of ultra-lightweight algorithms and mechanisms that execute in wearable devices to safeguard the integrity of the data.Read moreRead less
Using data mining methods to remove uncertainties in sensor data streams. This project will develop key techniques for removing uncertainties in sensor data streams and thus improve the monitoring quality of sensor networks. The expected outcomes will benefit Australia by enabling improved, lower-cost monitoring of natural resources and management of stock raising.
Effective and efficient record linkage with transformation rules. Record linkage is an enabling technology for organisations to identify and remove 'redundant' entries in their databases; this helps prevent data quality problems that may cost millions. This project will deliver the next-generation record linkage methodology that enables cost and time economical linkage beyond what is currently possible.
Extending fuzzy logic. Fuzzy logic is good for dealing with uncertain data somewhat like people do, and this technique has been used in train braking systems, computer animation etc, but can be slow for problems with large or complex data especially if the data are changing with time. The project will design efficient fuzzy logic algorithms capable of dealing with complex real world problems.
Deep Data Mining for Anomaly Prediction from Sensor Data Streams. Sensor data streams are crucial for anomaly predictions in real-life monitoring. However, balancing efficiency and accuracy in predicting anomalies with sensor streams is a great challenge; it requires new techniques that go beyond detecting anomalies and predicting trends. This project will develop a deep mining method for anomaly prediction from sensor streams; it will comprise mining algorithms at various levels - from compress ....Deep Data Mining for Anomaly Prediction from Sensor Data Streams. Sensor data streams are crucial for anomaly predictions in real-life monitoring. However, balancing efficiency and accuracy in predicting anomalies with sensor streams is a great challenge; it requires new techniques that go beyond detecting anomalies and predicting trends. This project will develop a deep mining method for anomaly prediction from sensor streams; it will comprise mining algorithms at various levels - from compressing massive raw data, to recognition of abnormal waveforms preceding anomalies, and to retrieving and summarising similar past anomalies for creating descriptions of future anomalies. The project will demonstrate our method in health/environment monitoring applications, and its adoption will save resources, money and lives.Read moreRead less