### Table 4: Distributions of Session Inter-Arrival Times: Summary.

"... In PAGE 5: ... A Pareto distribution was found to fit quite well both the body and the tail of the distributions. Table4 summa- rizes these findings providing the observed ranges of values for the mean, standard deviation and distribution parameters for the most... ..."

### Table 4: Distributions of Session Inter-Arrival Times: Summary.

"... In PAGE 5: ... A Pareto distribution was found to fit quite well both the body and the tail of the distributions. Table4 summa- rizes these findings providing the observed ranges of values for the mean, standard deviation and distribution parameters for the most popular file size ranges in each workload. 538... ..."

### Table 1. Statistics estimated from the distributions of number of messages with dif- ferent inter-agent link delay models

2002

"... In PAGE 12: ... We synthesize FGN from -stable distributions with parameters H = 0:75 and d = 0:4, Figure 7 shows the cumulative density functions (CDF) of time required to solve hard instances for AWC, ABT, and ABT with restarts, when all the inter- agent communication links have delays modeled as xed, negative exponential, and log-normal, with identical mean and di erent variances. Table1 and 2 show the estimated mean and variance of the number of mes- sages exchanged as well as the solution time for the di erent cases when the same instance is used for three algorithms. Delay distribution Mean Variance ABT ABT-rst AWC ABT ABT-rst AWC Fixed 1:8 105 1:2 105 8:2 102 3:6 1010 1:3 1010 3 105 Negative expon.... ..."

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### Table 1: Simulation Parameters for uniform distribution Mean arrival rate in a normal cell

"... In PAGE 6: ... Under normal condition (no network congestion), the average one-way communication delay between two MSSs is 2 mil- liseconds, which covers the transmission delay, the propagation delay, and the message processing time. Under uniform traffic distribution (shown in Table1 ), traffic in each cell is characterized by the mean arrival time, the mean service time, and the mean inter-handoff time, all assumed to be negative exponentially distributed. Non-uniform traffic distribution is modeled by a two-state Markov Modulated Possion Process, where a cell can be in one of two states: hot state or normal state.... ..."

### Table 1: Comparison of the equilibrium points under deterministic and statistical multiplexing. C = 30 Mbps. The over ow probability for the statistical multiplexing case is 10?6:5.

"... In PAGE 18: ... We have calculated such equilibria for a range of multiplexing capabilities of the network (by varying the amount of bu er B and by using the charging scheme based on the simple approximation, for over ow probability in the order of 10?6:5), and we compared them to the corresponding equilibria when deterministic multiplexing was used. We experienced a substantial increase of the utilization, Table1 . Of course, this is not surprising due to the very small mean rate of the inputs relative to their peaks and the capacity of the link (9 Kbps vs 30 Mbps).... In PAGE 18: ... This follows from the fact that, for large values of network bu er B, the indi erence curve G(d), for various values of shaping delay d, is not greatly a ected for the range of large apos;s ( gt; 100000 bytes), Figure 4. Furthermore, as we have noted in the previous section, the probable operating point (equilibrium) of the network (see Table1 ) will be in a range of large values of , hence the equilibrium point will not be a ected by the shaping delay d. Of course, using shaping, customers will make contracts with a lower peak rate h.... ..."

### Table 3 Descriptive Statistics And Zero Order Correlations Variables Mean s.d. 1 2 3 4 5 6 7 8 9

2007

"... In PAGE 24: ... The residuals from the six clustered regression with robust standard error models outlined in Table 4 were normally distributed. Results The descriptive statistics and zero order correlations can be found in Table3 . The test ... In PAGE 26: ...ommitment and turnover is -.41 (p lt; .001). Model 2 in Table3 suggests that introducing the commitment variable into the control variable model explains an additional 5% of turnover variance (p lt; .... ..."

### Table III. Correlations, means, standard deviations and correlations of all variables

### Table 3 Unconditional Daily Covariance and Correlation Distributions

"... In PAGE 11: ... Space constraints rule out providing a detailed characterization of each individual series. Instead, we report in Table3 the median value of the sample mean, standard deviation, skewness, and kurtosis for the covariance and correlations for each of the thirty stocks with respect to all of the twenty-nine other stocks; i.e.... ..."

### Table 2: Maximum Number of Multiplexable Voice Channels

"... In PAGE 9: ...1 1 50 100 150 200 250 300 Probability of Waiting Time gt; 4 ms (Varying Link Speed) Number of Channels 2x64 kbps 4x64 kbps 8x64 kbps 12x64 kbps 16x64 kbps 20x64 kbps 24x64 kbps 28x64 kbps 30x64 kbps Upper Limit Figure 3: Complementary Packet Delay Distribution In the following, we will review the questions issued in section Section 2. Table2 shows the maximum number of voice channels that can be supported given a certain link capacity (in multiples of 64 kbps). The resulting statistical multiplex gain is depicted in Figure 5.... ..."

### TABLE 1. Effects of age on immune parameters determined by correlation analysis

2003