Generalized Information Fusion and Scheduling for Effective Situational Awareness. Research on the generalized information fusion will lead to better surveillance,monitoring & situational awareness technologies that will significantly enhance our national security and contribute to the strategic directions set by the Nation. It will deliver generic integrated uncertainty reasoning models, algorithms and implementations and will lead to enhanced interoperation capability across multiple collabora ....Generalized Information Fusion and Scheduling for Effective Situational Awareness. Research on the generalized information fusion will lead to better surveillance,monitoring & situational awareness technologies that will significantly enhance our national security and contribute to the strategic directions set by the Nation. It will deliver generic integrated uncertainty reasoning models, algorithms and implementations and will lead to enhanced interoperation capability across multiple collaborating organizations that have surveillance and situational awareness as their prime responsibilities (defence, police and the road transport authority). It will position the nation to use its relatively small defence force to maximum effectiveness in combating terrorism, crime and natural disasters like Tsunami & Earth quakes.
Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100240
Funder
Australian Research Council
Funding Amount
$315,000.00
Summary
Geometry and Conditioning in Structured Conic Problems. Conic programming allows one to model and solve large industrial problems via modern optimisation methods, such as interior-point algorithms. These methods are efficient and reliable in solving a vast number of problems, however, they fail on a relatively small but significant set of ill-posed instances, thus affecting the overall reliability of the technique. The reason for such behaviour is profound and constitutes one of the major unsolv ....Geometry and Conditioning in Structured Conic Problems. Conic programming allows one to model and solve large industrial problems via modern optimisation methods, such as interior-point algorithms. These methods are efficient and reliable in solving a vast number of problems, however, they fail on a relatively small but significant set of ill-posed instances, thus affecting the overall reliability of the technique. The reason for such behaviour is profound and constitutes one of the major unsolved problems in real complexity: there is no known algorithm that solves conic problems with real data in polynomial time. The project aims to develop a deep understanding of the geometry of conic problems, aiming for the resolution of this fundamental problem in computational theory.Read moreRead less