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The generation of high-complexity microarray data has necessitated the development of novel data analysis methodologies that can cope with data of this nonlinear and highly dimensional nature.
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In this paper, we describe an inherent safety analysis methodology that can be applied in the early stages of process development.
Sierla et al. (2012) in their paper introduced a risk analysis methodology that can be applied at the early concept design phase, whose purpose is to identify fault propagation paths that cross disciplinary boundaries, and determine the combined impact of several faults in software-based automation subsystems, electric subsystems, and mechanical subsystems.
The research goal of this paper is to introduce a risk analysis methodology that can be applied at the early concept design phase, whose purpose is to identify fault propagation paths that cross disciplinary boundaries, and determine the combined impact of several faults in software-based automation subsystems, electric subsystems and mechanical subsystems.
Cluster analysis has several methodologies that can be used in heuristic manner for solving this type of problems.
Any breeding program must be periodically subjected to critical analysis with respect to its performance, seeking methodologies that can improve its effectiveness.
This method essentially converts any allopolyploid genome into a diploid genome regarding the software and methodologies that can be employed for genetic analysis.
Types of research questions and methodologies that can be addressed within the multilevel process analysis framework are described.
The combined Economic Value and Environmental Impact analysis is a multi-level methodology that can be used to represent biorefinery system performances as an aggregate of differential economic and environmental impact margins of biorefinery products.
Principal component analysis (PCA) is a statistical methodology that can be seen as unveiling the internal structure of the data in a way that best describes the variation in the data [ 30].
This research has provided an extended analysis to select the proper charging methodology that can be used to design an enhanced charging system.
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