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The choice of failure analysis methods was flexible.
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Hence, the existence of machine learning methods can overcome these challenges because machine learning methods are flexible in recognizing the gene-gene interactions that can contribute to individual's disease status.
The applied functionalization method was flexible in controlling the functionalization level.
The method was flexible enough to pick up variants that worked via any of the possible resistance mechanisms described above.
The method is flexible for use with other compression techniques.
Data mining method is flexible, however its potential to downscale the meteorological weather data is limited.
In particular, the proposed method is flexible to effectively sense the signals that are not stationary.
The projection method is flexible because it progressively adapts the linear approximation to any possible solution.
That means, the proposed method is flexible and adaptable to the existing conditions of each infrastructure.
The method is flexible, since it is simple to implement with the nonuniform knots.
The proposed method is flexible and easy to implement in any design problem.
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