Generating ratio

Defining contrast is obtained by multiplying the generating ratio by its associated factor. The defining contrast, the case, XiX2X3=X4 has the form l=XiX2X3X4. 

By multiplying the chosen generating ratio with new factor X3 we obtain the defining contrast 1=X X2X3. 

To illustrate this let us observe the FUFE 2s. In this case we obtain a half-replica of type 25 1, as given by the generating ratio X5=X1X2X3X4. The associated defining contrast is 1=X1X2X3X4X5, and aliased/confounded estimates are defined by these ratios ... 

Now consider the FUFE 1/16-replica for eight factors. In this case the design of type 28-4 is defined by four generating ratios ... 

These generating ratios have been used to construct the matrix X4=XiX2X3 X5=-X2X3... 

Determine aliiased/confounded effects in accord with generating ratios or defining contrasts ... 

To obtain the second-order regression model, second-order CCRD has been used. The number of design points (trials) for k=5 was 32. The design core has corresponded to half-replica 2s 1 with this generating ratio Xs=XrX2X3X4. The value and number of design points in the experimental center n0=6 are determined from Table 2.137. The design of experiments with outcomes is shown in Table 2.145. 

In optimization of the process of obtaining novocaine, FRFE 24"1 with generating ratio X XjXzXj was chosen for the basic design of experiments. The system factors are x,-time of reaction, min x2-temperature, °C x3-surplus of sodium salt of paraa-minobenzoic acid, % and X4-concentration of sodium salt of paraaminobenzoic acid, %. The system response is the yield of chemical reaction %. Outcomes of basic experiment with application of method of steepest ascent are shown in Table 2.191. 

Table 2.233 shows the design matrix and outcomes of experiments, with a remark that variation intervals are 2 times smaller and make up less than 10% of the factor space. The half-replica of FUFE 24 with generating ratio X4=XiX2X3, and one replication of the trial is realized once again. Besides, one trial has been done in the design center to estimate the significance of the sum of regression coefficients next to square members (2b i). The trial offered these values y10=13.37 y2o=14.83 y0=14.10. 

The Design matrix corresponds to FRFE 25 2, with these generating ratios X4=X1X2X3 and X5=XiX2. The outcomes of experiments are given in Table 2.238. 

The ratios of components both for 10 extreme vertices and for designs of experiments n=4 and 8 are given in Tables 3.7 and 3.8. Levels or ratios of components Xj, X2 and X3 in the design of experiment n=4 are generated from a fractional design 23 1 with generating ratio X3=XjX2, Table 3.9. 

The potential of wind energy to produce large-scale electric power is focused on the development of wind-turbine tower technology from current sizes of 1 to 3 MWe to turbines that will produce 3 to 5 MWe. The number of 5 MW wind turbines that could produce 9 PWh/a by 2050, estimated for an average electricity generating ratio of 3 GWh per installed MW (American Wind Association, 2007), would be about 600 000. These would be located in areas of sufficient mean annual wind speeds for commercial operation and as an auxiliary resource in other locations. 

Use the function ratio.calculate.log2 to generate ratios and log-transform the ratios base 2. This function works on probes of each transcript per running. 

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