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1. Open the Behaviors panel. 2. Select the object in the Document window or the tag in the Tag Selector to which your behavior is attached. 3. Double-click the action that you want to alter. The appropriate dialog box opens, with the previously selected parameters. 4. Make any modifications to the existing settings for the action. 5. Click OK when you are finished.

Style Selected Target > <!ELEMENT Address > <!ATTLIST Address Class ID Style > !Error !Error !Error

Figure 18.7 Structure for determination of piezoresistivity in diamond crystallites. The piezoresistor in this SEM micrograph contains only one grain boundary [66]. Reprinted with permission from Diamond and Related Materials, Analysis of piezoresistive properties of CVD-diamond lms on silicon by M. Adamschik, R. Muller, P. Gluche, A. Floter, W. Limmer, R. Sauer and E. Kohn, 10, 9 10. Copyright (2001) Elsevier

20 9 11 46 40 44

We all need to adopt a different attitude to the way we have historically viewed ourselves and our jobs. The industry has pigeonholed us into thinking of ourselves as account handlers or creative people who make TV spots or print ads, or direct marketers or sales promotion people, or PR people, or interactive people. We need to stop thinking of ourselves in that narrow light . . . and begin to think of ourselves more as general marketing practitioners whose job it is to develop the most powerful creative idea to move a client s business forward regardless of the medium. From a developmental concept, it s an exciting and empowering way to redefine our jobs. Marty Susz, Euro RSCG MVBMS, New York

5. If you want to display every record in the recordset, choose the Show: All Records option. 6. Click OK when you re finished.

Allele1 Chrom 1 Chrom 2 Chrom 3 Chrom 4 Chrom 5 Child 1 Chrom 7 Chrom 8 Child 2 Chrom 10 6 4 2 10 0 10 6 2 3 1 Allele2 6 1 10 4 7 4 2 1 4 4 Allele3 8 6 1 3 5 7 4 9 3 7 Allele4 1 10 2 7 8 9 3 5 7 9 Sum 21 7 5 24 6 30 15 7 11 19 Average Fitness 441 49 25 576 36 900 225 49 121 361 278.3

17:18

turned into the as-built so, rst as-planned, then as-planned plus the rst delay, used to quantify the effect of the second delay, then asplanned plus the rst two delays and so on; as-projected schedule used mid-project, which is as-built up to now and as-projected for the remainder of the project.

Depth (km)

Substituting Equation 4.87 into 4.84 and solving for DQ yields:

By undetermined coefficients we obtain yp The amplitude is C a2 b2 (2/9)2 (4/9)2; 20 / 9, _ cos 3t 2 9

The accompanying CD-ROM includes the samples as well as some of the software and reference material that we refer to in this book, including the Motorola J2ME SDK and the Research In Motion Java Development Environment. Refer to the index.html file at the root of the CD for all of the details. You can also refer to the book s Web site at www.ericgiguere.com/microjava for updates, corrections, and more material.

To a certain extent every algorithm involved with classi cation runs the risk of over tting the data. This is the phenomenon where the algorithm learns the errors (noise) in the data as well as the underlying structure of the processes that created the data. This phenomenon occurs because every algorithm attempts to reduce the error in classifying the data, and many algorithms including identi cation trees can reduce this error by introducing more and more splits in the data. When this happens the model can become overly complex, which in itself is not desirable due to the increase in model size, and therefore it cannot be interpreted as easily. However, a further effect is that the tree becomes so accurate on the training data samples that a new sample not seen previously by the identi cation tree is falsely classi ed. Essentially, the algorithm has learnt the training data too well in that it has learnt the erroneous data as well as the underlying patterns. To identify when this problem occurs, the data can be divided into two sets: the training set and the test set. The