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The study approach used six sigma methodologies that effectively serve as the problem solving in oil classification extracted from the complex mixtures of oil spilled dataset.
A ternary diagram based on the relative molecular compositions of C27 C28 C29 regular steranes (Fig. 3a) is a method commonly used to determine oil-to-oil correlation and oil classification (Peters et al. 2005).
Whereas an analytical point of view to report a result with the uncertainty is a correct way, to consider the uncertainty for the olive oil classification can give rise to confusion.
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Because a product of this type was not available, we created a probabilistic classification model of oil and gas resource potential to facilitate landscape-scale analysis.
Improving oil palm classification in the Peruvian Amazon by combining active and passive remote sensing data.
This study involves the use of quality engineering in oil spill classification based on oil spill fingerprinting from GC-FID and GC MS employing the six-sigma approach.
Results obtained from this study reveals that by employing six-sigma approach in a data-driven problem such as in the case of oil spill classification, good decision making can be expedited.
The results reported in this paper highlight some important aspects to be considered in the olive oil commercial classification.
Therefore, the way to report the FAEE content with the uncertainty can create confusion, when the olive oil commercial classification is required.
The values of most of these parameters were within the limits established by the EU Directives for olive and pomace oils but classification of the respective oils was not conclusive.
For oilfield aquifers classification, oil and water physicochemical properties are used.
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