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Particulate reflectance functions

Particulate-Reflectance Functions. Regression parameters for particulate-reflectance relationships are shown in Table III. [Pg.73]

For comparison purposes, regression parameters were computed for the model defined by Equations 6, 7, 8, and 10 and the model obtained by replacing In (1/R) in those equations by R. The dependent variable (y) is particulate concentration because it is desired to predict particulate content from reflectance values. Data from Tables I and II were also fitted to exponential and power functions where the independent variable (x) was reflectance but the fits were found to be inferior to that of the linear relationship. [Pg.76]

Figure 1 and 2 demonstrate the linear relationship of trash and dust content (wet assay) to both In (1/reflectance) and reflectance. The coefficient of determination (r ) is the percentage of total variation explained by the regression. For example, percentage of unexplained variation (i.e. 1.4% for y = trash content and 3.8% for y = dust content (wet assay) with x = reflectance) is indicative of a significant relationship between particulate content in cotton and In R. A small unexplained variation was observed for all of the trash and dust content functions in Table III. Airborne dust unexplained variation, however, was poorer precision of the measurement for the five cottons investigated was not reported. [Pg.76]

The orientation of bonds is strongly affected by local molecular motions, and orientation CF reflect local dynamics in a very sensitive way. However, the interpretation of multimolecular orientation CF requires the knowledge of dynamic and static correlations between particles. Even in simple liquids this problem is not completely elucidated. In the case of polymers, the situation is even more difficult since particules i and j, which are monomers or parts of monomers may belong to the same chain or to different Chains. Thus, we believe that the molecular interpretation of monomolecular orientation experiments in polymer melts is easier, at least in the present early stage of study. Experimentally, the OACF never appears as the complicated nonseparated function of time and orientation given in expression (3), but only as correlation functions of spherical harmonics... [Pg.101]

Using the same hypothetical particulate suspension as in Figure 2, the relative distribution of the total surface area concentration as a function of size for values of j3 ranging from 1 to 5 is shown in Figure 3. If > 3, the total surface area concentration of the particulate fraction resides predominately in the fine-size fractions below 10 /x.m. Control of the concentration of an adsorbed contaminant would thus require removal of fine-sized particles by appropriate solid/liquid separation processes. If, however, < 3, removal of coarser particulates (1 > 10 /x.m) may satisfy the effluent standards. The selection of solids/liquid separation processes will thus depend, in part, on the shape of the size distribution function, as reflected by the value of p. [Pg.314]


See other pages where Particulate reflectance functions is mentioned: [Pg.220]    [Pg.152]    [Pg.95]    [Pg.76]    [Pg.312]    [Pg.353]    [Pg.32]    [Pg.568]    [Pg.112]    [Pg.270]    [Pg.200]    [Pg.217]    [Pg.52]    [Pg.582]    [Pg.199]    [Pg.221]    [Pg.184]    [Pg.165]    [Pg.537]    [Pg.5]    [Pg.32]    [Pg.194]    [Pg.1016]    [Pg.95]    [Pg.301]    [Pg.37]    [Pg.84]    [Pg.241]    [Pg.142]    [Pg.239]    [Pg.23]    [Pg.84]    [Pg.1321]   
See also in sourсe #XX -- [ Pg.73 , Pg.75 ]




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