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In Figure 12, the green lines indicate the estimated path.
The estimated path model accounted for approximately half the variance in math reasoning.
The study employed structural equation modeling (SEM) techniques and estimated path models to improve understanding of the relationship between the built environment and vehicle emissions.
The localization algorithm considers the average power values, P j, measured at each reference node j, as shown in Table 2, which also shows the variance of the collected power samples, σ P j 2. Figure 9 Estimated path loss exponent.
In (5), N is the number of Rx locations, P i denotes measured signal level and (L_{{text {rx}}_{i}} phantom {dot {i}!}) the semi-empirically estimated path loss at the location of the i-th Rx, considering the Tx with P tx at T j. begin{array}rcl@ F vec{beta},j =frac{1}{N} sum_{i=1}^{N} left(P_{i}-left(P_{{text{tx}}} -L_{{text{rx}}_{i}} left vec{beta}left(T_{j}right)right)right)right)^{2}.
Estimated path coefficients for the model with two classes can be seen in Figure 1.> -wrap-foot> Notes.
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This error is defined as the difference between the estimated path-loss exponents and the actual ones.
This means that stations that experience the largest averaged estimated path-loss between each other that is lower than a threshold, are clustered together.
In this expression, the dispersed signal power factor, P s, refers to the variance of the received estimated path-power for first arrival from temporally dispersed signal in the case of Rayleigh propagation.
Figure 6 Estimated paths for three pedestrians.
The estimated paths, based on the point estimates (25), for these three pedestrians are shown in Figure 6.
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