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A method based on Doppler measurements for computing position and instantaneous velocity of moving objects in the surroundings of a robot using an original panoramic radar sensor was presented.
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There is no measurement for computing power.
In this article, we have proposed a novel measurement-based approach for computing the interference factor between two wireless radio channels.
In our GMF implementation, we use the unscented Kalman filter (UKF) [3,4] for computing the measurement update.
The rest is used for computing.
The formula for computing a variable APR.
The total residual of the array measurements is computed for KHOMC and for other outer core V p models (IASP91, Tanaka-1, Tanaka-3, ak135, SP6, and PREM), and the least misfit is obtained for KHOMC (Fig. 6c).
Standard deviation (STD) and coefficient of variation (CV) of Log2 signal ratios were calculated for each measurable triplicate spots, and the mean values of all repeated measurements were computed for each array.
Changes in EELV between consecutive measurements were computed for EELVWI-WO (ΔEELVWI-WO) and EELVCT (ΔEELVCT).
At the end of simulation, average on all the measurements is computed for each of the cells of the space.
The reliability of measurements was computed for treatment and control groups separately by using Cronbach's alpha (intra-class correlation coefficients).
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