Data size

Size selectivity is the most thorough method of expressing classifier performance under a given set of operating conditions. Cut size and sharpness can be calcinated from size-selectivity data. Size selectivity is defined by... 

A multivariate normal distribution data set with the variance and mean given by this i and x was generated by the Monte Carlo method to simulate the process sampling data. The data size was 1000 and it was used to investigate the performance of the indirect method. 

Their analysis showed that the signal peptides are characteristic for each localization site. However, it may not be a general phenomenon because the data size was rather small and because such differences do not seem to be used as sorting signals in E. coli. 

Aliasing in the remote dimension is truly worthwhile only if the sample concentration is high enough to collect only the minimum number of scans per increment required for proper coherence selection in other words, the acquisition is not S/N limited. If so, aliasing offers a proportional saving in acquisition time and data size for a given spectral resolution. 

In the directly acquired dimension the spectral window can be opened up to cover all frequencies of interest on both sides of the carrier with a proportional increase in the overall data size. As an alternative, it may be sufficient to open the (audio)filters to allow signals to alias to empty regions (if any) with no intensity loss. Carrier shift using time domain tools in data processing can be applied to restore a more convenient arrangement of the spectrum [10]. 

Aliasing in the remote dimension is most beneficial when the number of acquisitions for each increment can be kept to a minimum. Should the number of scans be increased beyond the minimum, opening up the spectral window in the remote dimension may be a better choice than increasing the number of scans per increment. However, this will result in a larger data size. 

Ref. Models Number of descriptors (set size)a Data description Methodb Data size Accuracy of predictions0 Predicted to observed correlation 2)11... 

Original data size After Phase I and II After Phase III... 

Table 13.5 summarizes the priority setting results for the two data sets using the NCTR Four-Phase system. When only the Phase I and II protocols are used, the system dramatically reduced the number of potential estrogens by some 80 to 85%, demonstrating its effectiveness in eliminating these most unlikely ER binders from further expensive experimentation. The Phase III CoMFA model further reduces the data size by about 5 to 10%. More importantly, the quantitative binding affinity prediction from Phase III provides an important rank-order value for priority setting. 

A cube of data sized (mxnxp) can be unfolded in three different directions along the row space, along the column space, and along the third direction of the cube, also called the tube space. The three unfolding procedures give a row-wise... 

Estimated Data Size, in Gigabytes, for Icosahedral Reconstruction of Different Particle Diameters at Different Resolutions"... 

Redaction Noise and of Data Size Using IMgital Filters... 

Selective experiments offer a significant simplification of experiments, and a reduction of dimensionality, instrumentation requirements and data size, and in some cases also of the experimental time. For instance, measurement of spin-spin couplings between rare spin nuclei may require instrumentation for triple resonance experiments, including a special probe. In many cases selective measurements offer simple solutions for these demanding experiments. 

Standard values of A are only tabulated for a few data sizes. As a consequence it is more difficult to choose a length for the window that would be neither too small nor too large. 

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