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The purpose of this study is to develop a stochastic method which analyzes production data to predict future performance and to estimate reserves probabilistically.
The subspace iteration method, which analyzes eigenvalue problems with the Jacobi method, is applied in the subspace formed by substitution of the total space basic vector with the subspace basic vector.
Through analyzing the energy flows of the five consecutive loops which extract energy from the conditioned spaces and rejects it to the environment, the global energy intensity index is first to be put forwarded and then the decomposition method which analyzes the influence of the specific consumption (e) and delivered fluid ratios (p) on global energy intensity is proposed.
This is mainly because, on one hand 3D Panel Method is a kind of Boundary Element Method, which analyzes 3D potential flow field using surface mesh, on the other hand ROM is in essence a type of Spectrum Method and its analysis is performed in the reduced order space created by POD.
For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms.
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However, our purpose in this study is to propose a method, which analyze rather small amounts of low-quality data from the slip on the plate interface beneath the ocean bottom.
It differs significantly from meta analysis methods, which analyze each dataset separately and pool summary statistics.
Traditional methods which analyze microarray data, have provided a rich source of information for IR event detection [ 5].
Large-scale identification of these sequence elements are based on computational methods which analyze multiple sequences simultaneously.
Computational methods, which analyze gene regulatory interactions on a genome-wide scale from high-throughput biological data, have flourished in recent decades [ 12- 14].
Such an approach captures variation between animals with age, as it screens individuals as opposed to most conventional methods which analyze populations containing large numbers of pooled animals.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com