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A central composite experiment was designed to systematically vary air velocity, side weight and fat thickness.
Another question was whether the MC18_28 sample exhibited proportional effectiveness in the composite experiment, when compared with MC18 and MC28 (superposition and homogeneity issues).
A central composite experiment design in combination with the response surface method (RSM) is more efficient than conventional experiment design and allows interactive effects of factors to be determined (Bandaru et al. 2006; Ghevariya et al. 2011).
Model I: star experiment design using a quadratic polynomial without cross-terms; Model II: minimum experiment design using a quadratic polynomial with cross-terms; Model III: composite experiment design using a quadratic polynomial with cross-terms.
The thermal/chemical performance of this new Heat Pipe Oscillatory Baffled Reactor (HPOBR) was compared to a conventional jacketed OBR JOBRR) using central composite experiment designs for an imination reaction between benzaldehyde and n-butylamine, in the absence of solvent.
Here, we report the preparation of FCDs with a photoluminescence (PL) quantum yield (QY) of 10.58% from peanut shells via one-pot pyrolysis treatment optimized by using a central composite experiment design.
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The combination of the lithology - brine - CO2 and cement carbonation models reproduces brine chemistry evolution observed during the carbonation phases of the composite experiments (Figures 8 and 9).
Flexure from third-point loading and direct uniaxial tension of the fiber reinforced composite experiments were conducted with quasi-static loads.
For composite experiments, HBLs were resuspended in keratinocyte culture medium (KCM); for invasion, attachment and proliferation assays, HBL cells were resuspended in serum-free invasion assay medium (SFIAM).
In this study, based on the integrated conductivity including conductivity and tensile strength) data obtained by carbon fiber/ABS resin matrix composites experiment, a predicting and optimizing model using genetic algorithm-least squares support vector regression (GA-LSSVR) was developed.
Several one-factor-at-a-time experiments followed by a composite factorial experiment were performed based on a two-step strategy: 1) identifying the domain of variation of the controlled variables; 2) finding the best choice of the set point.
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