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A field experiment conducted above an aqueduct pipe illustrates the proposed methods with real data.
This is the first work to compare the performance of heterogeneity feature detection statistical methods with real miRNA datasets.
Further investigations should be done to correlate results from monocular and binocular tests methods with "real life" situations during driving.
Therefore, it is valuable to compare performance among methods with real data and identify those that provide more accurate predictions.
Also, the comparison among the methods with real data is only possible if the network which the data was generated from is known.
We also contrast the methods with real data using two urine biomarkers, Interleukin 18 and Cystatin C. The computer simulation studies confirm that the ML procedure is superior to the data deletion and simple data imputation procedures.
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In order to benefit the multimodal images and their integration with other medical data, new analytical methods with real-time feasibility and scalability are required.
In this section, we report the performance of our synthetic method with real FPV videos.
The examinations in vitro and in vivo show the correct operation of the method with real tissue features.
Therefore, the proposed method with real channel estimation can even achieve a better performance than the methods in [12, 13] with ideal channel estimation.
(2) The proposed method with real channel estimation performs even better than the methods in [12, 13] with ideal channel estimation when SNR is high, e.g., when SNR is larger than 15 dB.
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