Special Research Initiatives - Grant ID: SR0354753
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
MESH: amalgamating innovative teams of cross-disciplinary collaborators for creativity in Media-arts, E-culture, Science and Humanities. MESH is a cross-disciplinary network that amalgamates a national array of sub-networks of research in digital arts, ICT and cross-cultural and policy negotiation. It boosts Australia's existing cross-disiciplinary strengths in Media-arts, E-culture, Science and Humanities by encouraging existing digital sub-networks to grow together via well-brokered communic ....MESH: amalgamating innovative teams of cross-disciplinary collaborators for creativity in Media-arts, E-culture, Science and Humanities. MESH is a cross-disciplinary network that amalgamates a national array of sub-networks of research in digital arts, ICT and cross-cultural and policy negotiation. It boosts Australia's existing cross-disiciplinary strengths in Media-arts, E-culture, Science and Humanities by encouraging existing digital sub-networks to grow together via well-brokered communications and demonstrations online and on-location. Progressively, MESH participants will discover existing harmonies whilst also inventing new languages and protocols leading to breakthroughs in cross-disciplinary collaboration and innovation. MESH encourages a 'paradigm shift' in digital research, realising the extraordinary potential that is ready but latent across Australia's arts and sciences.Read moreRead less
Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techn ....Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techniques but also deliever effective solutions to a number of real-life apllications.Read moreRead less