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This classification is on the basis of occurrence and storage of groundwater.
The overall accuracy of correct classification is, on average, 92.64% ranging from 78% to 100% (Table 4).
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We could then calculate how accurate the cross-classification was on average when a given sensor participated in classification.
The classification is based on the information on the category, time, and location of complications.
The classification stage consists of the signal classification which is based on RBF networks while the image classification is based on MLP networks.
The classification is based on injury criteria defined by the law on Swedish patient injury.
First layer classification is based on MA techniques, whereas second layer classification is based on design objectives and characteristics of MAC protocols.
First layer classification is based on multiple access techniques, whereas second layer classification is based on design objectives and characteristics of MAC protocols.
This classification is based on their relationships to each other, as far as they are known.
This classification is based on the anatomical form of the articular surfaces.
Another classification is based on the object as in whaling, salmon fishing, and sponge fishing.
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