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Just like setting keyframes, tweening creates a smooth transition from one frame to another by applying the change over a series of frames. Notice that there is only a very slight amount of change in the first ten frames of the transition.
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The single most noticeable change in the Windows XP interface is the revamped Start menu (see 16 for complete coverage of this menu). Even though many people find the new Start menu more useful than the old, many don t. Fortunately, you can change back to the older style Start menu at any time. In fact, you can flit back and forth between the two if you like.
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Will your metrics work in the real world with real people We all know of people who game the system, explicitly lying or manipulating numbers rather than stepping up to a culture of performance. I ve seen a division of an F1000 company go bankrupt and end up sold because upper management and the sales management team allowed gaming in the posting of sales numbers. I ve seen contractors manipulate their project management numbers to make bonuses even though they must have known they would be caught in the end. Gaming happens when the organization s culture, executives, and management allow it to happen. As long as gaming is allowed, no performance management system will work effectively.
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Figure 8.16 (c) shows baseline details for diverse measurement and reconstruction data. The plot 1 baseline is the experimental data, which has slight noise features on the baseline. The plot on the 2 baseline is the reconstructed data from (b). The 3 baseline shows the reconstruction obtained from 130 projections if the baseline noise is thresholded off of the experimental data prior to simulated measurement. The 4 baseline shows the reconstructed data from the noisy experimental data if 200 projections are used. The 5 baseline shows the reconstruction from 100 projections, and the 6 baseline shows the reconstruction from 90 random projections. The random projections used the normal distribution measurement operator generated by the original l1magic program. As illustrated in the gure, estimated signal degregation is rapid if the sample density falls below a critical point. Note that each sucessive trace in Fig. 8.16 is shifted to the right by 1 nm to aid visualization. A second example uses the TV objective function and the two-step iterative shrinkage/thresholding algorithm (TWIST) [20]. As discussed in [76], the original iterative shrinkage/thresholding algorithm combines maximum likelihood estimation with wavelet sparsity. We brie y review maximum likelihood methods in Section 8.5.2. For the present purposes, we simply treat TWIST as a blackbox optimizer of the TV objective. We use TWIST to consider again the 4 downsample shift code. Rather than force model consistency with the full measurement operator, however, we focus on
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Proof: The existence of the factorizations was proved prior to the statement of the lemma. It remains to establiph uniqueness. We show this for one of the factorizations. A similar argument applies to the other factorization. Thus, a\tume that M = = L2L3 (B.4) are two Cholesky factorizations for M . Then
The Video and Audio Effects palettes, shown in Figure 2-10, enable you to quickly apply audio and video effects. Both palettes provide a grab bag of useful effects. For instance, the Video palette includes effects that change an image s contrast, and that distort and blur images. The palette effects are organized into folders. For instance, the Distort folder features effects that distort clips by bending or pinching.
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