Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less
Novel Characterization of Porous Structure and Surface Chemistry of Carbon. The aim of this project is to develop novel characterisation methods that probe the structure and surface chemistry of carbons, ranging from highly graphitised thermal carbon black through ordered mesoporous carbon to disordered porous activated carbon. The project plans to develop a new generic molecular model based on wedge-shaped pores. Conventional parallel sided pore models fail to account for real structures and th ....Novel Characterization of Porous Structure and Surface Chemistry of Carbon. The aim of this project is to develop novel characterisation methods that probe the structure and surface chemistry of carbons, ranging from highly graphitised thermal carbon black through ordered mesoporous carbon to disordered porous activated carbon. The project plans to develop a new generic molecular model based on wedge-shaped pores. Conventional parallel sided pore models fail to account for real structures and therefore for the physics of adsorption in real materials. The project then plans to back the theoretical model with high-resolution experimental measurements. It is expected that the model will unify the structural analysis for all carbons and account for all experimental isotherms within a rational and physically plausible framework.Read moreRead less
Efficient structure search over large graphs. The project aims to develop advanced search technology to support large-scale graph applications. The success of the project not only brings a breakthrough in technology development but also provides training for high quality personnel in this important and growing area, and brings considerable economic and social benefits to Australia.
Managing Hydrate Formation for Viable CO2 and Energy Transport. Increasing the allowable water content during the pipeline transportation of carbon dioxide (CO2) would greatly increase the viability of carbon capture and storage but would also increase the risk of CO2-hydrate blockages. Subsea methane (CH4) hydrate sediments represent a tremendous new energy resource if blockages in production pipelines can be avoided. Conventional oil industry approaches to hydrate avoidance are of limited rele ....Managing Hydrate Formation for Viable CO2 and Energy Transport. Increasing the allowable water content during the pipeline transportation of carbon dioxide (CO2) would greatly increase the viability of carbon capture and storage but would also increase the risk of CO2-hydrate blockages. Subsea methane (CH4) hydrate sediments represent a tremendous new energy resource if blockages in production pipelines can be avoided. Conventional oil industry approaches to hydrate avoidance are of limited relevance and too expensive for these new applications. Formation probability distributions, cohesive forces and agglomeration tendencies of CO2 and CH4 hydrates are intended to be measured and integrated into predictive multi-phase flow models, enabling quantitative risk assessments of blockages in CO2 transport or hydrate production pipelines.Read moreRead less