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Figure 7-15: A grid with no horizontal grid lines and vertical lines set at 10 pixels so objects snap to 10-pixel increments

30 25 20 15 10 5 0 2

The hydrolytic resistance test described in this chapter is the powdered glass test and not the water attack test as described above; see Appendix <661>, USP 27 [1].

Store all circuit boards flat in their box until they are needed. This is the best way to protect them from damage.

Therefore,

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To create a single EJB, it is necessary to create and manage many source files (such as the home interface, the implementation, the local interface, the descriptor, and so on ) even before counting the support classes that need to be created and managed. Best practices in Java EE development recommend creating applications out of fine-grained reusable components, and this exacerbates the proliferation of source files even for the smallest Java EE project. Ironically, most of these required files are essentially boilerplate code that is very tedious to create and maintain. Extremely sophisticated tools can be used to generate and maintain such boilerplate code, but for most J2EE 1.4 developers these tools are often inaccessible because of cost or resource constraints. (There are exceptions, such as the open source XDoclet tool.) Any practicing J2EE 1.4 developer can attest to the project complexity originating from the complex nature of the EJB 2.x model.

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and hence, (3.121) and (3.122) Then, by (3.115), the variances of the elements sol and sol of the Fisher score vector are (3.123) and (3.124) For Design 1, the variances (3.123) and (3.124) are equal to 0.0020 and 7.34 x lo3 and, for Design 2, to 0.0039 and 1.45 x lo4, respectively. These results show that the variances with Design 2 are nearly twice as large as those with Design 1, as could have been expected. For either design, 500 sets of Poisson observations with expectations (3.120) have been simulated next. From each of these sets, the Fisher scores (3.45) have been computed for 81 and 82. Histograms of these Fisher scores are shown in Fig. 3.2. As predicted, they are wider as the number of observations increases while their clustering around the origin agrees with (3.18). rn In 4, we will return to this increase of the variance of the Fisher score with the number of observations.

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In this case, however, the phasors of the nonlinear current Ig,n are analytically computed from the powers of the voltage Fourier series (see the probing method for the Volterra series), without any Fourier transform. In fact, the current phasor computation requires a good deal of formalism, but it can be easily handled by suitable numerical arrangements. The rest of the procedure is similar to the standard harmonic balance method, and the nonlinear equation system is formally identical to eq. (1.77) or eq. (1.90). The method is called spectral balance because only manipulations of spectra are involved, and no time-domain waveforms are computed [66 70]. The method is very ef cient especially for multi-tone input signal, up to several tens of input tones. By way of illustration, the spectral regrowth of a pseudorandom modulated signal is shown in Figure 1.37. Both the input and the output to the nonlinear system are shown, as computed by a multi-tone spectral balance algorithm.

The integrand is an odd function of z, and the integration limits are symmetric about the point z = 0. Immediately we conclude that ES(2) = 0 in this particular case. Thus, we conclude that Simpson s rule gives the exact result when f (x) is a cubic polynomial. Hermite interpolation (considered in a general way in Section 6.4) is polynomial interpolation where not only does the interpolating polynomial match f (x) at the sample points xk but the rst derivative of f (x) is matched as well. It is useful to interpolate f (x) with a cubic polynomial that we will denote by r(x) at the points (a, f (a)), (b, f (b)), and (c, f (c)), and also such that r (1) (c) = f (1) (c). A cubic polynomial is speci ed by four coef cients, so these constraints uniquely determine r(x). In fact r(x) = p(x) + (x a)(x b)(x c) for which = 4[p(1) (c) f (1) (c)] . (b a)2 (9.48a)

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