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Chen et al. [10] have claimed the NP-hardness of the problem, and proposed the shortest data aggregation (SDA) algorithm.
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The correlation coefficient between KCTD and NMS09 is blank due to the short data length.
Hence, the short data set constrains not to involve further influencing variables.
However, such an analysis is not possible on the short data sequences, whether the situation is stationary or not.
The results also show that the shorter data fusion interval used, the higher accuracy can be achieved.
This technique has many advantages; however, the main limitation in the real time context comes from the short data acquisition time for the needed wavelength range.
Whenever sampling was incomplete in one data set under comparison, the data set that sampled more months was truncated to match the sampling period of the shorter data set.
IR spectroscopy on the contrary had been challenged to its limitations with statistic means because the short data acquisition times characteristic for IR spectroscopy are well suited for multivariate data analysis of high numbers of spectra.
Mice with the lowest Hx levels survived the shortest time (data not shown).
One reason for favouring the CCT investigation is the significant shorter data acquisition time.
Shortest data aggregation.
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