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m is a home state in SRG iff {m | m m} is a home space in RG (ie iff m1 GM , s | m1 [s > m and m M) If M0 is a home state in the SRG and if each transition appears on at least one arc of the SRG then the marked net (W N, m0 ) is live The expressions of these properties must be slightly modi ed to be extended to the case where |M0 | = 1 [CHI 93] Other interesting properties may be obtained by extending the SRG construction For instance, s 10 and 11 of this book show how to exploit the SRG to estimate performances of stochastic well-formed nets 83 Colored invariants We have seen in 3 the usefulness of place invariants in the (structural) analysis of Petri net models.

After a maximum number of five slots, the right to use the channel expires and is automatically returned to the master even if there is still data waiting in the slave s output buffer to be sent Afterwards, the master device can decide if the channel is granted to the same or a different slave device If the master did not receive any user data from the slave and the master s output buffer for the particular slave is also empty, it can pause the data transmission for up to 800 slots in order to save power As the duration of a slot is 625 microseconds, 800 slots equal a transmission pause of 05 seconds See Figure 63 for an example As a slave cannot anticipate when a new packet of a master arrives, a slave is thus not able to establish a connection to additional devices.

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The cross-dimension feature is available for most reports in Google Analytics. You ll see it in three places depending on the type of report: below the main graph on the left side (see Figure 7.4), below the main graph to the right next to other drill-down and Data Selection options (see Figures 7.5 and 7.6), or in the column headings in the report Data Table (see Figure 7.7). Additionally, custom reports use

In ordinary Petri nets, the computation of linear invariants can be conducted with the help of resolution of the system equations induced by the incidence matrix of the net: variables of this system are places of the net, while equations de ne the incidence of the transitions on these variables Solving this system can be done with the help of the Gauss algorithm or with the help of the Farkas algorithm when positive constraints are added to the coef cients of the solutions With the help of these algorithms we obtain a generative family of invariants which can generate any invariants of the net by linear combinations of elements of the family..

We can thus write I ( s) as follows:

Table 11.8 Distribution for Cm Ca Cb assuming the causal model of Table 11.7 cost ( k) 16 18 20 22 24 computation 0.6 0.8 0.8 0.6 0.8 0.2 0.6 0.2 0.8 0.6 0.2 0.2 0.4 0.1 0.1 0.4 0.1 0.9 0.4 0.9 0.1 0.4 0.9 0.9 probability 0.384 0.192 0.028 0.072 0.324

In some cases, it is therefore necessary that master and slave change their roles during the lifetime of the piconet This is necessary for example if a PDA has established a connection to a PC in order to synchronize data As the PDA is the initiator of the connection, it is the master of the piconet While the connection is still established, the user wants to use the PC to access a picture file on a mobile phone and thus has to include the mobile phone in the piconet This is only possible if the PDA (master) and the PC (slave) change their roles in the piconet This procedure is called a master slave role switch After the role switch, the PC is the master of the piconet between itself and the PDA.

C. K. Prahalad and Gary Hamel, The Core Competence of the Corporation, Harvard Business Review (May June 1990), 81. 9 Dorothy Leonard-Barton, Core Capabilities and Core Rigidities: A Paradox in Managing New Product Development, Strategic Management Journal 13, Special Issue: Strategy Process: Managing Corporate Self-Renewal (Summer 1992), 113. 10 Harold Demsetz, The Theory of the Firm Revisited, Journal of Law, Economics and Organization 4, no. 1 (Spring 1988), 148.

(1.114)

"Cannot mix next bar prices with data streams other than data1."

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