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However, regression models of site productivity seldom explain much more than 50% of the variability due to the difficulty in measuring many of the environmental variables which affect tree growth, particularly variables associated with soil fertility.
It is based upon those variables which affect the problem.
There are some variables which affect the latency parameter.
In our proposed solution for routing in WMN, we have three types of variables which affect the resolution of problem.
The variables which affect the preconcentration were optimized using a 23 factorial design and central composite design (CCD).
Special attention is paid to critical variables which affect the measured strength, such as loading geometry and specimen size.
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First, in screening experiments fractional factorial design (FFD) was used for selecting the variables which affected the extraction procedure.
A two level full factorial design 2k was used for selecting the variables which affected the extraction procedure.
Each site was different in terms of terrain, location, accessibility, and many more variables which affected the overall operations and the time needed to complete them (Fig. 2).
Variables which affected mosquito density were analysed using the univariate generalized linear model.
The temperature of expression and the concentrations of tryptone and kanamycin were the three variables which affected productivity.
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