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The results of Experiments 1 and 2 indicate that parallel perceptions of multiple attribute pairs lead to recognition of a multiattribute object, and that object recognition is not necessarily based on unified object representations.
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Another exclusive prediction of our hypothesis is that multiple attribute-pair representations are stored in memory, which could cause specific errors in a short-term memory task.
We therefore conclude that our results support the paired-attribute model, suggesting that attributes of an object are integrated with one another to form multiple attribute-pair representations and that many cognitive processes are based on the network of these representations rather than unified object representations.
Decisions on attribute weights are important problems in multiple attribute decision making.
WP is a relative simple multiple attribute utility methods.
This is particularly true if multiple attribute fields in the source data need to be considered.
It extends earlier work on design of experiments in the presence of within-pair order effects for a single qualitative attribute and fills a void in the recent design literature on choice experiments with multiple attributes.
A node can have multiple attributes, and each attribute can be set to a value.
This option may be specified multiple times to specify multiple attributes.
A self-developed WRMA (Weighted Rating of Multiple Attributes) method is used to rate attributes.
Multi criteria decisions and multiple attributes are considered.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com