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The proposed algorithm is performed on HEVC reference software HM16.12.
Evaluation of proposed algorithm is performed on OMNeT++v4.3 [89] simulator using a simulation testbed.
Evaluation of the proposed algorithm is performed on a benchmark problem for HDD track following.
The proposed algorithm is performed on some standard datasets with appropriate accuracy and lower time complexity in comparison to the other state-of-the-art algorithms.
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Compared to previous methods, our proposed algorithm is performed very fast based on the simple ordinal measure of accumulated motion.
Based on this result, the proposed algorithm was performed with threshold values of the motion activity in the range of 10 to 30.
The sequence alignment method in the proposed algorithm was performed using BLASTP [ 21].
Considering that the proposed clustering algorithm is performed on a long-term time scale, the computation cost for the proposed clustering algorithm is manageable.
Considering that the proposed clustering algorithm is performed on a long-term time scale as described in Fig. 10, the computation cost for the proposed clustering algorithm is manageable.
The proposed algorithm is also performed by a cluster head.
The effectiveness of the proposed algorithm is confirmed by fatigue tests performed on ST3 steel compact tension shear specimens in the full range of mode mixities from pure mode I to pure mode II.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com