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Numerous methods have been suggested to detect the multivariate outliers.
There are different methods suggested to detect the existence of multicollinearity problem between the model explanatory variables.
The inspection and monitoring techniques suggested to detect and/or predict each failure mode are described in Section 2.2.
In this article, a new data pre-processing method has been suggested to detect and classify vertebral column disorders and lumbar disc diseases with a high accuracy level.
Other techniques have been also suggested to detect and classify the states of eyes including distinctive features of eyes, such as corners and coloured sections of the iris.
A combination of kjeldahl and spectrophotometric method has been suggested to detect milk adulteration by melamine, urea and ammonium sulphate (Virginia de Lourdes et al. 2013).
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In addition, Maslach and Leiter [ 6] suggest to detect burnout at an early stage and prevent the full blown development of burnout.
A wide range of criteria have been suggested to automatically detect wear time and non-wear time for uniaxial accelerometers.
To date, BCRP expression is suggested to be detected at the highest level in B-lineage ALL, although no definite trends were shown between BCRP expression and prognosis of ALL [72], [73].
Likewise, endothelial dysfunction has been suggested to be detected very early in the life of insulin resistant subjects despite a lack of significant structural changes, indicated by a thickening of the intima-media layer [ 16].
Manual methods have been suggested to be efficient to detect back pain ([31], [32].
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