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The judges evaluated the projects in categories of usability, manufacturability, safety, prototype effectiveness, and presentation effectiveness.
The categories of usability return on investment (ROI) have a similar model.
Two broad categories of usability methods exist: those that gather data about the behavior of actual users and those that can be applied even without users present.
Analysis by severity of problems found and diminishing return analysis model on the relationship between the number of new problems discovered with users and evaluators used showed that both methods are equally efficient and effective in addressing different categories of usability problems.
In the same way, various decision trees are attained for different categories of usability data.
Axial coding was performed to develop connections among the categories of usability problems.
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Attribute selection i.e. InfoGainAttributeEval with Ranker algorithm is implemented on the content category of usability data.
Figure 3 represents a partial view of collected data belonging to the content category of usability data.
Table 4 represents a comprehensive list of association rules belonging to the content category of usability data.
Table 5 represents obtained decision tree after applying the ID3 algorithm on the content category of usability data.
The highest variation in local weights of needs was found in the category of Usability (Table 2).
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