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Traditionally, measures have been developed using classical test theory (CTT).
Some excellent models have been developed using classical thermodynamics and modern molecular dynamics.
Theoretical methods for calculating electric fields and IR vibrational shifts in enzymes have been developed using classical MD and mixed quantum mechanical/molecular mechanical (QM/MM) approaches.
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This questionnaire was developed using classical methodology in the following three phases over a two-year period: Item Generation phase, identifying all possible items having adverse impact on the QOL of RTR, Item Reduction phase, selecting the most pertinent items related to QOL, and Validation phase, analyzing the psychometric properties.
By far, most health outcome measures have been developed using methods from classical test theory (CTT).
The formulation is developed using the Classical Laminated Plate Theory (CLPT) and Donnell's equations, solving for the complete displacement field.
Traditional holistic face recognition algorithms are developed using the classical statistical techniques such as the principal component analysis (PCA), linear discriminant analysis (LDA), and canonical correlation analysis (CCA) [12].
This simple result is developed using the classical plate theory and is shown to hold true when higher order plate theories or the three dimensional elasticity theory is used.
In this paper, a generalized semi-analytical approach for lateral-torsional buckling of simply supported anisotropic, thin-walled, rectangular cross-section beams under concentrated load at mid-span/mid-height was developed using the classical laminated plate theory as a basis for the constitutive equations.
In this paper, a generalized analytical approach for lateral-torsional buckling of simply supported anisotropic hybrid (steel-FRP), thin-walled, rectangular cross-section beams under pure bending condition was developed using the classical laminated plate theory as a basis for the constitutive equations.
A risk adjustment model was developed using a classical single-level regression.
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