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The same steps are necessary for the other prede ned entities listed in Table 31-1. Instead of using the markup shown under the heading Markup Equivalent, you can also use the Unicode values shown in the next column. Every character in any language you use (with a few rare exceptions involving comparatively obscure languages) can be represented by character references, which are Unicode values mapped to characters (a process described earlier). For example, if you wanted to write out the word Foo, you could write it like this:

Bits 0 7 of the state member contain flags that specify the tree view item s state. Bits 8 11 of the state member give the one based index of the item s overlay image. Bits 12 15 of the state member give the applicationdefined state image.

* Each participant (e.g. cardholder) in the SET system possesses two pairs of RSA keys: one for generating

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Figure 12.17: Bit error rate as a function of Eb/No of R = 1/2, K = 5 convolutional code with different quantization levels and decoding window lengths (following [ 1481). Figure 12.18 shows the effect of the quantizer threshold spacing A on the performance for an 8-level quantizerwith a K = 5, R = 112 code and a K = 5, R = 1/4 code. The plots are at SNRs of 3.3 dB,3.5 dB, and 3.7 dB (reading from top to bottom) for the R = 1/2 code and 2.75 dB, 2.98 dB,and 3.19 dB (reading from top to bottom) for the R = 1/4 code. (These latter SNRs were selected to provide roughly comparable bit error rate for the two codes.) These were obtained by simulating, counting 20,000 bit errors at each point of data. A convolutionalcode can be employed as a block code by simply truncatingthe sequence at a block length N (see Section 12.9). This truncation results in the last few bits in the codeword not having the same level of protection as the rest of the bits, a problem referred to as unequal error protection. The shorter the block length N , the higher the fraction of unequally protected bits, resulting in a higher bit error rate. Figure 12.19 shows BER for maximum likelihood decoding of convolutional codes truncated to blocks of length N = 200, N = 2000, as well as the "conventional" mode in which the codeword simply streams.

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CO~SU~ER(Tc=~) = (item -> DELAY[l] I tick -> C O ~ S U ~ E R ) , DELAY[t:I..Tc] = (t==Tc) tick-3 C O ~ S U ~ E R (t<Tc) tick-> DELAY[t+l]

You can also use selectors to match elements by class. Why would you want to do this Suppose that you had two areas on your page with different backgrounds, one light and one dark. You would want the light background area to have dark text and

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