The phrase "applying this assumption" is correct and usable in written English.
You can use it when discussing a hypothesis or premise that you are incorporating into an analysis or argument.
Example: "In our analysis, we are applying this assumption to evaluate the potential outcomes of the experiment."
Alternatives: "utilizing this assumption" or "incorporating this assumption".
Applying this assumption, the red marrow absorbed dose per unit-administered activity is 29 mGy/kBq.
By applying this assumption, which, in practice, is always satisfied automatically, the data can be easily divided into smaller groups with similar properties.
Applying this assumption, the intensity of the band increase of ratio I288/I305 and its correlation with our results (the decrease of the ratio I331/I337) was established.
Later in this section, we will compare the theoretical results with simulation results to show that our derivation by applying this assumption also works when the bandwidth of bandpass filter is much greater than bandwidth of low-pass filter.
When applying this assumption to the phenomenon of intensive policing, it is not surprising, I would argue, that a country that has the highest rate of gun ownership among Western countries, the highest murder rate by guns among advanced democracies and the largest military apparatus in the world would see a militarization of its police.
Applying this assumption, the resulting cost for all 90,623 hospitalizations was €62.05 million annually.
However, it may be difficult to apply this assumption to practical systems because of the limitations of the current transceiver design.
Yaguchi et al. [9] applied this assumption to 3D camera and proposed the fast and lightweight method to construct 3D environment model of the room.
Out of the 221 genes, only 10 contribute to disease only through change-of-function mutations (COMP, FGFR2, GFAP, NOTCH3, PSEN1, RYR2, SCN4A, STAT3, UMOD, and TTR) implying that we can apply this assumption to a majority of genes in our data set.
Therefore, different from the original state transition: S i = f(S i-1 ), in which the current system state S i depends on the system state of the last step S i-1, our new approach does not apply this Markov assumption, and instead S i = f(S i-1, S i-2, … S 1 ), which could present a history-dependent dynamics.
