Rezvani, S, Prasad, G, Muir, J and McCraken, K (2003) Interactive Feature Extraction From Multivariate Production Data. In: 3rd International Workshop on Pattern Recognition in Information Systems, PRIS 2003. 3rd International Workshop on Pattern Recognition in Information Systems, PRIS 2003. 12 pp. [Conference contribution]
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Abstract
As part of a research programme between the University of Ulsterand a polymeric manufacturing company, the interrelationships andperformance attributes of polymeric components used in adhesivesmanufactured for medical packaging are being studied. To understand theinteractions between the parameters, to select the optimal manufacturingprocesses and to improve economic factors within this investigation, a series ofmultidimensional data processing and visualisation methods such as PrincipalComponent Mapping (PCM), Curvilinear Component Mapping (CCM) andSammon Mapping have been examined. As a novel approach to multivariatedata visualisation and analysis, these techniques were employed in such a waythat interactive multi-layer maps could be generated. Each layer within thisfeature extraction technique corresponds to a specific attribute andcharacteristic of the dataset. Activation and superimpositions of individuallayers allow studying manufacturing attributes, parameter interactions andproduct formulations,
Item Type: | Conference contribution (Paper) |
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Faculties and Schools: | Faculty of Computing & Engineering Faculty of Computing & Engineering > School of Computing and Intelligent Systems Faculty of Art, Design and the Built Environment Faculty of Art, Design and the Built Environment > School of the Built Environment |
Research Institutes and Groups: | Computer Science Research Institute > Intelligent Systems Research Centre Computer Science Research Institute |
ID Code: | 18497 |
Deposited By: | Professor Girijesh Prasad |
Deposited On: | 16 May 2011 10:46 |
Last Modified: | 20 May 2011 14:27 |
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