S-RMSemantically Reliable Multicast
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To this end, this work attempts to acquire the reasonable shear gap of S-RM in the direct shear test, which is meaningful to obtain the more realistic strength.
The first aspect of size effect in S-RM is the particle size distributions (PSDs), which can be applied to predict its mechanical and physical properties.
where R is the certain particle size, r is the granular size of S-RM, A is the cumulative area of particles whose sizes are over R, [C.sub.a] is the shape factor, [[lambda].sub.a] is the largest particle size, and D is the fractal dimension of granularity.
Meanwhile, the total mass of S-RM M(r > 0) is presented as follows:
The fractal presentation of S-RM can be obtained as follows [25]:
First, three predictive models, WA, S-RM, and M-RM, which are constructed based on result of the Bayesian estimation model, for yam shape prediction are compared in terms of MSE.
Three predictive models we applied were weighted average (WA) and single and multiple regression methods (S-RM and M-RM, resp.).
Caption: FIGURE 6: The MSE value for three predictive methods: WA (dotted line), S-RM (broken line) and M-RM (solid line).
Isolates, S-RM and 6-RM, were inoculated 1.5% v/v to the two flasks containing media while other served as control.
Isolate 6-RM and S-RM were grown in 100 mL of MS medium for 24 h.
From the partial sequencing of 16S rRNA, the isolates used in this study were identified as Stenotrophomonas maltophilia (S-RM) and Bacillus subtilis (6-RM).
Nature and characteristics of phenol degrading enzyme from S-RM and 6-RM