Sentence examples for a new normalization from inspiring English sources

To simplify the computation of eigensensitivity, a new normalization of the general nonlinear eigenproblem is presented.

In this regard, we employ interval arithmetic and introduce a new normalization technique based on interval distance of interval numbers.

In response to this perceived gap, the development of a new normalization technique is considered in this paper that provides an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and objective weighting in materials selection.

This article presents a complementary analysis that includes a new normalization of the generalized Hoek Brown failure criterion, complete solutions for associated and non-associated flow rules, with some new closed-form solutions in the latter case, and in-depth considerations regarding intermediate stresses and edge effects.

However, a new normalization technique is needed to take account of goal values in target-based MADM techniques.

In Section 2, we give a new normalization method and the iteration-covering procedure, which are very important to obtain the main result.

So, we applied a simple, new normalization approach by selecting different interaction thresholds of contacts in order to get similar topology of networks for the four cells/cell lines.

By introducing an additional and new normalization condition, we construct two extended systems of linear equations with nonsingular coefficient matrices which are transpose to each other.

Our method employs a new global normalization method (nonparametric empirical Bayes correction normalization) [ 14- 17], utilizes pre-defined enriched regions identified from single-sample enriched regions identification programs, uses statistical methods to define differential enriched regions, then defines binding pattern information for those differential enriched regions.

Our method employs a new global normalization method: nonparametric empirical Bayes (NEB) correction normalization, utilizes pre-defined enriched regions identified from single-sample peak calling programs, uses statistical methods to define differential enriched regions, then defines binding (histone modification) pattern information for those differential enriched regions.

Here, we generated seeding points in an equivalent way by renormalizing the probability density (Equation 8) on each cap individually as (15) P Σ (s i | h 0 i, k i ) = 1 A   p ˜ Σ (s i | h 0 i, k i )  , wherein the new normalization factor A is obtained by integration over only one parabolic cap (16) A (h 0 i, k i ) = ∫ ​ dΣ i   p ˜ Σ (s i | h 0 i, k i )  .