Results 31 to 40 of about 471,125 (347)
The purpose of this paper was to introduce the fractional factorial design and its quantitative data analysis of variance and the SAS implementation. The fractional factorial designs were very similar to the factorial designs and the orthogonal designs ...
Hu Chunyan, Hu Liangping
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The present work sheds light on the potentiality of proteins extracted from oak (Quercus robur) leaves to treat both drinking water and industrial oily wastewater.
Abderrezzaq Benalia+8 more
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Improving MPI and hyperthermia performance of superparamagnetic iron oxide nanoparticles through fractional factorial design of experiments. [PDF]
Li Y+10 more
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The optimization of the supercritical fluid extraction (SFE) of cannabinoids, using supercritical carbon dioxide (scCO2), was investigated in a fractional factorial design study.
S. Qamar+3 more
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This paper aims to investigate the mechanical properties of specimens printed by 3D open-source printers. It discusses the effect of five factors (part orientation, layer height, extrusion width, nozzle diameter, and filament temperature) on the ultimate
Amna Mazen+2 more
semanticscholar +1 more source
Construction of Optimal Split-Plot Designs for Various Design Scenarios
When performing fractional factorial experiments in a completely random order is impractical, fractional factorial split-plot designs are suitable options as an alternative. It is well recognized that the more there are lower order effects of interest at
Beichen Han, Yuna Zhao
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Split-Plot Designs with Few Whole Plot Factors Containing Clear Effects
Fractional factorial split-plot designs are widely used when it is impractical to perform fractional factorial experiments in a completely random order.
Yuna Zhao
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Piroxicam belongs to BCS class II and has low solubility. Self-nanoemulsifying drug delivery systems (SNEDDS) are considered a potential approach for increasing the solubility and release of piroxicam.
Septiawan Adi Nugroho+2 more
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Neural Network Assisted Experimental Designs for Food Research
The ability of artificial neural networks (ANN) in predicting full factorial data from the fractional data corresponding to some of the commonly used experimental designs is explored in this paper.
H.S. Ramaswamy+4 more
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