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Looking at the sum a little closer, we nd that it is made up of coherent pairs since, for each product ei ej that occurs in multiplying one set of voltages by the other, there is a second identical product ej ei . One pair arises from ei in the rst distribution and ej in the second, and the other arises from ej in the rst distribution and ei in the second.2 The voltages add for the two members of each coherent pair whereas the powers add when the various pairs, which are not coherent with each other (i.e., their phase relationships are random), are added. Therefore, the result has twice the power density that it would if everything were noncoherent. [Adding the two members of a pair gives a power four times the individual powers, rather than two times, as noncoherent addition would give. Thus the summation of voltage that occurred for coherent signals (cosines) implies twice the summation of powers.] Therefore, we integrate the product of input PSDs to get a resulting PSD and double the result in recognition of the coherent pairs: S2 (f ) S0 (f ) S0 (f ) =2 , (5.5) 2 2 2 where correlation is indicated by the pentagram and the prime differentiates this function from the same function after it has been multiplied by appropriate constants. This correlation is the same as convolution, since S(f ) = S( f ). As f approaches zero, the correlation becomes equal to the integral of a constant [S0 (0)/2]2 over a width of 2B, so Eq. (5.5) gives S2 (0) = 4B 2 S0 2

xi / D wi for all i If both constraints 0 x / D v C w for all i are active, then there are and such that u i Ni i i Let pi D vi , D wi or D vi C wi , in line with the three possibilities described above Then the point x, at which f is maximized within A, can be characterized as the N solution to k problems, the ith of which is to maximize [u i xi / pi xi ] over xi Note that these k problems decouple and can be solved in a decentralized fashion The ith problem is to be solved by agent i He seeks to maximize his net bene t, given that the price per box of type i is pi .

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Object diagrams are used to exemplify a class diagram. These diagrams can show objects, the name of the objects, the object states, and links (instances of relationships) among the objects. Statechart diagrams are used to express which states a class object can have. They also show what triggers the change from one state to another. Activity diagrams are used to describe activities and actions taking place in a system. These diagrams are used in this book to describe business processes (i.e., to describe the activities taking place in an organizational system). Sequence diagrams show one or several sequences of messages among a set of objects. Collaboration diagrams describe a complete collaboration among a set of objects. Use-case diagrams and their attached use-case text specifications are used to describe system functionality. Component diagrams are a special case of class diagram used to describe components within a software system. Component diagrams are not used in business modeling. Deployment diagrams are a special case of class diagram used to describe hardware within a software system. Deployment diagrams are not used in business modeling. This chapter did not touch upon patterns in UML. Patterns are described in detail in 6, Business Patterns. The object constraint language, OCL, is discussed further in 5, Business Rules. This chapter also did not address those areas of UML not relevant to business modeling. A more comprehensive description of UML can be found in our previous book, UML Toolkit (New York: John Wiley & Sons, Inc., 1998). The next two chapters provide more detail on how UML can be used and adapted for business modeling. Though the material in these chapters is based on standard UML, the UML extension mechanisms are used to adapt the language to better suit business modeling.

Thus the problem of maximizing the function f can be solved in a decentralized fashion, within a market for services where this optimal price vector will be determined Observe that in most cases, pi = p j equals i = j , so prices are proportional to effective bandwidths This is the main motivation for using effective bandwidths in pricing Note that in the original model, xi denoted the number of boxes of type i that are placed in the elevator We can extend the model and assume that the elevator takes one unit of time for each trip Now xi denotes the rate at which boxes of type i are served We can make the analogy to networks by thinking of services as boxes and the network as an elevator This is a valid analogy since services consume network resources, of which networks have nite amounts.

We saw in section 4.2.3 that the phase-to-phase fault clear of earth is:

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