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The development of efficient algorithms for measuring sequence similarity is an important goal of bioinformatics.
This fact is useful for development of efficient algorithms for crosstalk cancelation.
The development of efficient algorithms to analyze complex electromagnetic structures is of topical interest.
The development of efficient algorithms for representing, manipulating and rendering complex and large datasets is a challenge of volume visualization.
A challenging task of volume visualization is the development of efficient algorithms for representing, manipulating and rendering complex and large datasets.
The overall novel contribution of this research is the development of efficient algorithms for the simultaneous solution of the state equations.
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Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena.
In this paper, we focus on the development of new efficient algorithms.
Moreover, this work also motivates the development of more efficient algorithms for the MSMP problem.
Accordingly, development of more efficient algorithms would be desired to solve the proposed inexact nonlinear models (Sahinidis [2004]; Zhou et al. [2008]; Zhou et al. [2009]).
This has led to the development of more efficient algorithms.
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