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so m is smaller by N at the output where the frequency is smaller by N . A single-sideband contaminant, at the input to a divider, that has amplitude r relative to the signal there, has equivalent FM sidebands with relative amplitude of r/2 and will produce sidebands of relative amplitude r/(2N ) at the divider output. The output, and possibly the input, will not be a sinusoid. This relative sideband level applies to the harmonics at the output as well as the fundamental, but the effective divide ratio to a harmonic is smaller by the harmonic number [e.g., the relative amplitude at the third harmonic of the output would be r/(2N/3)]. Example 8.12 Frequency Divider Spectrums at Input and Output Figure 8.22 shows the spectrums at the input (a) and the fundamental output (b) of a 5 frequency divider with FM on the input. The input FM sidebands are at 46 dBc. This might represent decomposition of a 40-dB single sideband. The modulation frequency is fm = 1 kHz, so the spectral lines are offset 1 kHz from the input carrier. The output carrier is at one fth the input frequency. The FM sidebands there are still offset 1 kHz since the modulation frequency does not change in frequency division. Since the deviation has been reduced by 5, however, the modulation indexes are reduced by 5 also, so the relative sidebands are lower by (8.16) 20 dB log10 (5) = 14 dB.

Advanced Segments are best used when answering business questions for example, Should we expand our physical locations to a certain area, say, Portland, Oregon Based on this business question, you can create Advanced Segments that provide further insight into the Portland area and fuel the analysis of whether expansion into that area is a good business decision. Note how this approach is different from asking a direct numbers question such as How many visits did we get from Portland If that is the question you use to approach Advanced Segments, you of course can create a segment that provides that number. However, you could have already accessed that particular number via the Geographic reports in Google Analytics. The business question Should we expand our physical locations to a certain area, say, Portland, Oregon requires the analyst to create a more complex segment, or multiple segments, and analyze the resulting data at a much deeper level than had a nonbusiness question such as How many visits did we get from Portland been asked.

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framework of production systems modeling, the structure of marked graphs allows detection of regularities in the time dynamics of the system. More precisely, for strongly connected graphs, it is possible to determine the cycle time and the flow rates, but also to characterize the final state in stationary mode. These methods are mainly based on the decomposition of the graph into elementary circuits. The disadvantage of these methods is that all the elementary circuits and paths must be determined explicitly, and the complexity of this computation is exponential. For the analysis of discrete event systems or hybrid systems, it is however possible to use other methods [CAS 00, BAC 92, DEM 02, DAV 05], complementary to graph theory. Let us mention, for example, the use of linear programming, dioid algebra, stochastic processes, and automata approaches. The improvement of performance evaluation methods to optimize manufacturing systems can be achieved by comparing the various models of marked graphs presented in this chapter. For example, while replacing stochastic variables by their average, the deterministic model thus obtained is a bound of the stochastic model. Another aspect of the improvement consists of extending the existing models towards hybrid system theory. Indeed, the combination of discrete aspects and continuous aspects in the same formalism increases the modeling and analysis power for performance evaluation of manufacturing systems.

5.3.5. Marking graph and class graph In a class graph, various classes may exist with the same marking, but with different time domains. This simply means that the transition related time information generally modifies a net behavior. This fact will be illustrated in a very simple time Petri net, assuming only one single marking, by observing the effect of various time-interval assignments to transitions. In the first example, Figure 5.4, the trivial interval [0, [ is associated with each transition. The net s class graph is then isomorphic to its marking graph (see theorem 5.1). All firing sequences constructible with t1 and t2 are firable from the initial class.

The traditional four Ps of marketing, Product, Placement, Price, and Promotion, were subjected to massive depreciation in the last few years None of them now provide a sustainable differentiation that justifies loyalty and customer commitment Although companies are still laboring to provide good products and competitive prices available at many locations and promoted through multiple vehicles and media, none of these efforts registers as special in customers minds Companies often allocate the vast majority of their resources to these traditional Ps, only to find themselves at par with customer expectations At par means undifferentiated and therefore not preferred Any new product launched in the marketplace is subject to significant and ever growing competitive forces The uniqueness of the product will wear off much sooner than it would have 20 years ago.

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