Sensor measures specific variable (K), have a nonlinear output and are valued for a limited range....

     

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Sensor measures specific variable (K), have a nonlinear output and are valued for a limited range. So when the Sensor is manufactured, the manufacturer supplies a resistance (R) vs. the variable (K) curve. An accurate representation of the curve is generally given by \(K= \alpha + \beta \cdot In(R) + \gamma \cdot (In(R))^2 \) Where a, ß and y are constants of the calibration curve. Given the following values for the Sensor R K 1101.0 298.263 911.3 303.281 636.0 313.27 451.1 323.278 The value of variable (K) for a measured resistance of 907 ohms most nearly is **Use 4 decimals for calculations.* ** You have been given the following data show in table 8.1 8.5 19.3 7.7 X y based on these data, find the f(x)dx using Simpson 3/8 Rule 1.1 8.5 8.0 The table below shows the fourth and fifth approximations for the root of the function f(x) x6 ? ? X fx x4 4.84 3.1 x5 7.75 2.3 the value of the sixth approximation (x6) using the Bisection method is Sensor measures specific variable (K), have a nonlinear output and are valued for a limited range. So when the Sensor is manufactured, the manufacturer supplies a resistance (R) vs. the variable (K) curve. An accurate representation of the curve is generally given by \(K= \alpha + \beta \cdot In(R) + \gamma \cdot (In(R))^2 \) Where a, ß and y are constants of the calibration curve. Given the following values for the Sensor R K 1101.0 298.263 911.3 303.281 636.0 313.27 451.1 323.278 The value of variable (K) for a measured resistance of 907 ohms most nearly is **Use 4 decimals for calculations.* ** You have been given the following data show in table 8.1 8.5 19.3 7.7 X y based on these data, find the f(x)dx using Simpson 3/8 Rule 1.1 8.5 8.0 The table below shows the fourth and fifth approximations for the root of the function f(x) x6 ? ? X fx x4 4.84 3.1 x5 7.75 2.3 the value of the sixth approximation (x6) using the Bisection method is

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