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9: Working with Digital Media
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Table 26-8: Protected Instance Methods of the Control* Method Name Description events are generated. This method calls the control's parent's method of the same name. This method is called before the ProcessKeyMessag e method is called to determine whether the parent processes the message. ProcessMnemonic Processes a mnemonic character. Refer to the IsMnemonic method. Forces a re-creation of the handle for the control. Converts the current alignment to the necessary alignment to support right-t o-left text. Identical to the previous function, except not in a protected scope. Converts the current horizontal alignment to the appropriate horizontal alignment to support right-t o-left text. Converts the current left-right alignment to the appropriate leftright alignment to support right -to-left text. Scales the entire control and any child controls by the ratio specified. This prevents the programmer from having to scale each control individually. Activates the control if the CanSelect property is true. Sets the bounds of
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where local.h is the name of the local function header file.
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One of the most commonly abstracted mechanisms of WordPress is the user and authentication system. This class ports the WP_User class to BP_User and carries most of that same system with it. It applies to a specific user object. The class.wp-users.php file contains methods that will work with the user system as a whole.
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FIGURE 1.1 Problem solving vs. innovation
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The Frame part is a weldment. Weldments are discussed in detail in s 31, 32, and 33. They are made of multiple bodies within a single part file. Multiple bodies are discussed in detail in 26.
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MASTERING MULTIMEDIA WITH WINDOWS VISTA
Non-planar Parting Surfaces
Figure 2.17 Alternative drawing of an active mixer with MOSFET Gilbert cell.
observations. Conceptually, this is highly unpleasant, and the recommendation derived from finite sample theory makes eminent sense. Problems with uninformative observations of course become serious only if there are very many such low-leverage observations. But they appear also in multiparameter regression, and, paradoxically, even in the absence of high leverage points. For a nontrivial example of this kind, see the discussion of optimal designs and high breakdown point estimates near the end of Section 11.2.3. It seems that these problems, which become acute when the (asymmetrically) contaminated distributions defined in (10.37) overlap, have been completely ignored in the robustness literature. Yet they correspond to a fact well known to applied (non-)statisticians, namely that by increasing the number of uninformative garbage observations, one does not improve the accuracy of parameter estimates (it may decrease the nominal estimated standard errors, but it also may increase the bias), and, moreover, that observations not informative for the determination of a particular parameter should better be omitted from the least squares determination of that parameter. To avoid possible misunderstandings, I should stress once more that the preceding discussion is about outliers in the yi, and has little to do with robustness relative to gross errors among the independent variables. We shall return to the latter problem in Section 7.12.
Streit. J . [l961 ..................... 110 Strom. E.G. [61] .................... 11 Stuber. G.L. [292] .................. 193 Suda. H . [95] ....................... 29 Suda. H . [l081 ..................45. 75 Sugimoto. H . [l411 .................. 85 Sugimoto. H. [ 1471..................85 Sugimoto. H . [ 1441 ..................85 Sugimoto. H . [ 1371.................. 85 Sugimoto, H . [l481 ..................85 Sun. S.M. [l411 ..................... 85 Sun. S.M. [l451 ..................... 85 Sun. S.M. [l421 ..................... 85 Sun. S.M. [ 1441 ..................... 85 Sun. S.M. [l371..................... 85 Sun. S.M. 11481..................... 85 Sunaga. T. [87] ..................... 24 Sunay. M.O. [ 1021 . . . . . . . . . . . . . . . . . .30 Suoranta. R . [ 1831 ..... .96-98. 1 1 1. 112 Suzuki. H. [49] ...................... 7 Suzuki, T [l701 ..................... . 91 Svensson. A . [ 1921 .................109 Svensson. A . [l891 ................. 109 Swales. S.C. [2] .. .O. 124. 125. 127. 132. 134.193.22 2-224 Swales. S.C. 1191........... .O. 126. 134 Swales. S.C. [223] .................123
using one-step RTP only. The Mo doping + low-dose PAI has the best resistance
TABLE 13.1
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