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This study aims to explore modular inequalities of interval-valued fuzzy soft sets characterized by Jun's soft J-inclusions.
This paper focused on exploring modular inequalities of IVF soft sets characterized by Jun's soft J-inclusions.
Here we propose several basic inequalities of IVF soft sets characterized by IVF soft inclusions, which are useful in subsequent discussions.
Simulated data sets characterized by various types of known non stationarities are used for validation of PGA and for comparison of its performance to other methods.
The internal coordinate vector for any given crystal can be symmetry reduced and can be grouped into various sets characterized by identical growth rates.
As a continuation to this line of research, in the present paper we will focus on modular inequalities of interval-valued fuzzy soft sets characterized by Jun's soft J-inclusions.
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These sets characterize the fault diagnosability.
Combining descriptor sets, such as the feature-based ProtFP (Fature) with the physicochemical property-based descriptor set Z-Scales (3), small but consistently improved model performance, which is likely due to the different way these descriptor sets characterize amino acids.
A PCA analysis was again performed to connect these observations of descriptor set performance to the similarity of the sequences and the way the descriptor sets characterize the space.
Our data helped identifying gene sets characterizing the sequential differentiation steps from stem cells to fully differentiated adipocytes.
However, developments in DNA microarray technology have allowed the generation of genome-wide data sets characterizing experimentally the regulatory networks of corynebacteria [ 18- 20].
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