High accuracy in long computational intervals and the stability of the approximated solutions encourage us to apply a similar method for solving other applied mathematics problems (see, for instance, [31]) in the future.
However, because the methodology per se is general, one approach to this issue is to apply a similar method to other types of Omic data (such as proteomic and metabolomic data) when similar repositories become available.
In this study, we apply a similar method using nonlinear three dimensional finite element analysis in the design process of a cementless stem for Malays.
The Republicans then applied a similar method to see whether someone registered in New Jersey was also registered in one of five states: New York, Florida, Pennsylvania, North Carolina and South Carolina.
Now, applying a similar method to that opted in (i) to identity (9), we obtain the desired results.
Applying a similar method to the proof of Theorem 5.2, we obtain an unbounded component (mathscr{D}^{nu}subset Sigma^{nu}) with ((0,0 in mathscr{D}^{nu}).
In this section, we examine if applying a similar method in presence of interference results in an accurate approximation of PER.
Since G is convex, by applying a similar method as in Theorem 1, we deduce that L z, t) is subordination chain.
Recently, based on applying a similar method to the one employed by Gut and Spătaru [7], a result related to the precise asymptotics in the law of the iterated logarithm for R / S statistic was established by Wu and Wen [19], that is, we have the following.
In addition to reviewing some of the human perceptual theories underlying graphical interfaces for information visualization systems, Schmidt and Stock (2009) applied a similar method of using tags to express basic emotions such as anger, disgust, fear, happiness and sadness in images.
Proof of Theorem 1.1 Applying a similar method to prove [[8], Theorem 3.2] with obvious changes (we only need to replace g ( t, u ; μ ) with ξ ( u ) in the proof of Lemmas 3.1, 3.2 and 3.4 of [8]), we can obtain the result of Theorem 1.1.
