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Data collection was achieved by MSE methodology using two interleaved scan functions with independent collision energies.
A numerical methodology using two different leader channel criteria has been implemented.
This study illustrated a design methodology using two decision techniques for achieving optimal product architecture.
This work suggests a simplified methodology using two types of biofeedback equipment adapted to semi-natural situations.
This work presents a study of robustness applied to a previously proposed fluorescent methodology using two replicated 27-4 saturated fractional factorial designs.
We verified the accuracy of our methodology using two different previously published datasets that used the Affymetrix Nsp 250K arrays.
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In another method, proposed by Swain and Lenka, a steganography methodology using four LSB arrays is suggested.
In Section 5, we illustrate our methodology using three case studies, namely, a pipeline A/D converter and two RF front-ends, for UMTS and UWB receivers.
Finally, we conduct an experimental analysis with the proposed methodology using six well-known benchmark databases of software projects, where two relevant performance metrics and a fitness function are used to assess the performance of the proposed methodology, which is compared to classical machine learning models presented in the literature.
Our methodology uses two radiative transfer models that operate at leaf (PROSPECT) and canopy (DART) levels.
The methodology uses two computer-aided design tools: AIDA, a multi-objective multi-constraint circuit optimization tool, and SIDe-O, a tool that characterizes and optimizes integrated inductors with high accuracy (around 1% when compared to electromagnetic simulations).
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