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try, type of revolver, commitment size, and percent utilization) were not found to be suf ciently signi cant. Using the preceding estimated regression equation, Araten/Jacobs predicted LEQs. These predicted LEQs are shown in italics in Exhibit 3.28. In his review of this section prior to publication, Mich Araten reminded me that, when you want to apply these LEQs for a facility with a particular maturity t, you have to weight the LEQ(t) by the relevant probability of default. The reason is that a 5-year loan s LEQ is based on the year it defaults; and it could default in years 1, . . . , 5. If the loan defaults in year 1, you would use the 1-year LEQ, and so on. In the unlikely event that the probability of default is constant over the 5-year period, you would effectively use an LEQ associated with 2.5 years. Industry Studies S&P PMD Loss Database While the S&P PMD Loss Database described earlier was focused on recovery, it also contains data on revolver utilization at the time of default. This database provides estimates of utilization as a percentage of the commitment amount and as a percentage of the borrowing base amount, if applicable. All data are taken from public sources. S&P PMD has indicated that it plans to expand the scope of the study to research the utilization behavior of borrowers as they migrate from investment grade into noninvestment grade. Fitch Risk Management Loan Loss Database The Fitch Risk Management (FRM) Loan Loss Database can be used as a source of utilization data as it contains annually updated transaction balances on commercial loans. In the FRM Loan Loss Database, the utilization rate is de ned as the percentage of

In addition to technical features and theoretical performance, there are many other important considerations to take into account when choosing a CODEC for a practical application. These include industry support for the CODEC (for example, whether there are multiple sources for technology), availability of development tools and costs (including development, integration and licensing costs). In this chapter we discuss the requirements of a selection of applications and consider practical issues that may affect the choice of CODEC. We list some of the available commercial MPEG-4 Visual and H.264 CODECs and report the claimed performance of these CODECs (where available). We review important commercial considerations (including the contentious topic of patent licensing) and end by making some predictions about the shortand long-term developments in CODEC research and standardisation.

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Sawyer, D. T., Sobkowiak, A., Roberts, J. L., Jr, Electrochemistry for Chemists, 2nd edn, Wiley & Sons, New York, 1995. 2 Mann, C. K., in Electroanalytical Chemistry, Vol. 3 (Ed. A. J. Bard), Marcel Dekker, New York, 1969, p. 57. 3 Bauer, D., Breant, M., in Electroanalytical Chemistry, Vol. 8 (Ed. A. J. Bard), Marcel Dekker, New York, 1975, p. 281.

Let us assume as usual that from an observation it is known that attribute A has value a4 . Obviously the corresponding (conditional) possibility distribution can be determined from the three-dimensional distribution by restricting it to the slice corresponding to A = a4 , that is, by conditioning it on A = a4 , and then computing the marginal distributions of that slice . This is demonstrated in Figure 3.15. Note that the numbers in the slices corresponding to other values of attribute A have been set to zero, because these are known now to be impossible. Note also that in contrast to the probabilistic case the numbers in the slice corresponding to A = a4 are unchanged, that is, in the possibilistic case no renormalization takes place. However, as in the probabilistic case studied in Section 3.3.2, distributions on two-dimensional subspaces are also sufficient to draw this inference; see

It is not just repeat business from one IP address that is worth monitoring; almost all customer behaviour whilst accessing an on-line shop or service can be of value. Although we have tended to concentrate on Web server statistics, because they are commonly gathered and understood, there is no reason why other sources of shopping behaviour cannot be analysed in the same way. User behaviour can also be monitored on the client (the

One example of generating spurious messages is the so-called source routing attack. On the Internet, the TCP/IP protocols are themselves very trusting. They are more concerned with ensuring the reliability of the connection than with its authenticity. This has opened up the possibility for a particular form of source routing attack, which allows a third party to pretend to be someone else, even without being able to observe the traf c across the network. Consider what happens when a TCP/IP session is initiated:

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Until relatively recently, fashion had always been litist and was used by its adopters to show that they were above the common people. Even the inventions of the eighteenth and nineteenth centuries; the spinning jenny, the water frame and the sewing machine have not had as great an effect on the market as have cultural changes and the explosion of the media during the twentieth century.

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