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The supernatants were analyzed by radio-TLC and HPLC using the abovementioned methods for quality control.
The quality of the watermarked speech signal obtained using the abovementioned methods was evaluated based on SNR and PESQ.
Using the abovementioned methods, we were able to segment cross sections along the entire vocal tract.
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Using the abovementioned simulation, the authors examined the model (DMHP).
This assumption was experimentally confirmed using the abovementioned images.
Irradiation was carried out using the abovementioned xenon light source.
The 30-band data set was classified using the abovementioned augmented training set.
Rotation-translation scans were performed employing several w values and ranges of optimal w were determined using the abovementioned criteria.
Prediction models using the abovementioned scales are presented.
SCSMV was detected in the field samples using the abovementioned primers.
Therefore, once the intra-sentential language patterns for cause and effect events are generated using each of the abovementioned methods, the next step is to generate inter-sentential language patterns by finding frequently co-occurring patterns between the cause and effect text spans.
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