Waiting times

The characteristic time of the tliree-pulse echo decay as a fimction of the waiting time T is much longer than the phase memory time T- (which governs the decay of a two-pulse echo as a function of x), since tlie phase infomiation is stored along the z-axis where it can only decay via spin-lattice relaxation processes or via spin diffusion. 

Elevators with decreased wait time, making intelligent floor decisions and minimizing travel and power consumption... 

It is interesting to note here that the delay time of a customer in the system depends also upon the number of customers arriving after him and upon the probability that they collude with him or with customers ahead of him. How to describe and relate the variables entering in the computation of this waiting time is another problem that should be considered. 

Justify this expression for W. Note that both L and W enable one to make decisions about the amount of waiting space needed and as to whether better and faster service is required in order to shorten the waiting time. 

As we have previously seen the theoretical expression for the average waiting time is given by... 

Waiting time, average, 318 Walter, J., 768 War gaming problems, 252 Wave equation, Schrodinger (See entries under Schrodinger)... 

Fig. 18.2H FT spectra of the alignment echo for different waiting times t2 and different temperatures. Sample LPE, amorphous fraction...

The expression in Eq. (29) can be evaluated numerically for all values of t, and the results for three different waiting times are shown in Fig. 11 for c = 0.1. The value of Tmin = 2.0 ps at E/To = 5.7 x lO", derived from the present theory (also consistent with Goubau and Tait [101]) was used. The results for t = 10 ps demonstrate that, due to a lack of fast relaxing systems at low energies, short-time specific heat measurements can exhibit an apparent gap in the TLS spectrum. Otherwise, it is evident that the power-law asymptotics from Eq. (30) describes well Eq. (29) at the temperatures of a typical experiment. 

Tests were carried out with apparatus volumes that varied between 8 and 12000 cm3, ait decreased and the self-ignition waiting time increased when the volume increased. The following AIT extreme values and waiting time (t) for the three compounds below were ... 

Often it is necessary to influence the setting time, either by accelerators or by retarders. If a cement is to be placed into a shallow depth, then acceleration of setting will be desirable to avoid unnecessary waiting times. On the other hand, in a deep formation more open time is required, which may require the addition of retarders. 

In reality, the queue size n and waiting time (w) do not behave as a zero-infinity step function at p = 1. Also at lower utilization factors (p < 1) queues are formed. This queuing is caused by the fact that when analysis times and arrival times are distributed around a mean value, incidently a new sample may arrive before the previous analysis is finished. Moreover, the queue length behaves as a time series which fluctuates about a mean value with a certain standard deviation. For instance, the average lengths of the queues formed in a particular laboratory for spectroscopic analysis by IR, H NMR, MS and C NMR are respectively 12, 39, 14 and 17 samples and the sample queues are Gaussian distributed (see Fig. 42.3). This is caused by the fluctuations in both the arrivals of the samples and the analysis times. 

Fig. 42.4. The ratio between the average waiting time (iv) and the average analysis time (AT) as a function of the utilization factor (p) for a system with exponentially distributed interarrival times and analysis times (M/M/1 system).

Fig. 42.6. Probability that the waiting time is smaller than < (t given in units relative to the average analysis time).

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