Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications ....Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications including consistency checking and spatial query pre-processing. The project will help in extracting knowledge from massive spatial databases, meeting the growing needs of naive users for spatial information and establishing Australia as a major player in spatial cognition research and in the development of geo-location services.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347079
Funder
Australian Research Council
Funding Amount
$160,000.00
Summary
Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufact ....Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufacturing - in particular sheet metal components for the automotive industry. The facilities will enable a database of dimensional and strain information to be established in support of related manufacturing R&D projects.Read moreRead less