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Figure 10.12: A process uses the use cases an information system supplies. The use cases are implemented by components in the information system.

Conditions can be combined into logical statements using AND and OR operators; for example, Where City matches Portland and Region matches Oregon. To put this concept of Advanced Segments into a tangible perspective, think about it as a pack of Skittles candies. Without segmentation, you just have a pack of candy. But apply segmentation based on the criterion of color matches purple





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philosopher x getting a rst fork, indexed by x for the left one and x + +1 for the right one. Then he waits either in place PwaitR or PwaitL for the second fork, until he gets it (transition getR2 or getL2), to reach stage Peat. Finally he gives back the forks (transitions putL then putR2 or putR then putL2) before returning to state Pthink. For four philosophers the reachability graph shows 341 states and 1160 arcs. It is possible that both philosophers 1 and 3 (or conversely both 2 and 4), succeed in eating simultaneously, but there are also the two known deadlock nodes. 7.5. Other high level formalisms We have studied colored nets and well-formed nets. Other formalisms also allow us to enrich the token semantics of a Petri net, while still offering some veri cation techniques. Of these we will brie y look at interpreted nets and algebraic nets [REI 91]. 7.5.1. Interpreted nets In a colored or well-formed net, data associated with the studied system are modeled with places and color domains. Therefore the same formalism is used to model both the control and the data, which allows an integrated analysis but leads to the construction of complex domains.

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Fig. 5.3 Exponential and linear decline in fraction surviving (s) with density (N). Notice the change in shape with increasing values of a (see text for details). The intercept of the exponentially declining function can be easily altered (dashed line).

where r is a uniform random number and T is a variable analogous to temperature. Otherwise, the new variable set is rejected. Thus, even if a variable set leads to a worse cost, it can be accepted with a certain probability. The new variable set is found by taking a random step from the old variable set pnew = dpold (7.2)

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