### TABLE III SCALED ENDPOINT ERRORS WITH PRRT PLAN

2007

Cited by 1

### TABLE III SCALED ENDPOINT ERRORS WITH PRRT PLAN

2007

Cited by 1

### TABLE 17. ERRORS IN ESTIMATES OF BOUNDARY FOR MODIFIED ANSCOMBE PROBLEM

1983

### Table 3 Comparison of measured corner wear and predicted corner wear using different polynomial networks

1998

"... In PAGE 5: ... A comparison of measured corner wear and predicted corner wear using the two polynomial networks (Figs. 3 and 4) is presented in Table3 . The average absolute error between the measured corner wear and the predicted corner wear using the polynomial network with torque is 25.... ..."

### Table 6: Blocking probabilities for the long (i.e., multi-hop) and short (i.e., single hop) flows: The blocking probabilities of the short flows at each of the three congested links are listed separately. The last column indicates the blocking probabilities that would result from assuming that the acceptance probability for a long flow is the product of the acceptanceprobabilities at each hop. The data is for =0. The relevant comparisons are between the product approximation and the actual blocking probability of the long flows; comparing the absolute blocking probabilities between the MBAC and the endpoint designs is misleading because the parameter values are not tuned to give equivalent loss rates.

2000

"... In PAGE 11: ... The question we have is whether endpoint admission control experiences more severe discrimination against multi-hop flows. Table6 shows the blocking probabilities for the two classes of flows. The MBAC blocking probability is well mod- eled by the product approximation.... ..."

Cited by 83

### Table 6: Blocking probabilities for the long (i.e., multi-hop) and short (i.e., single hop) flows: The blocking probabilities of the short flows at each of the three congested links are listed separately. The last column indicates the blocking probabilities that would result from assuming that the acceptance probability for a long flow is the product of the acceptanceprobabilities at each hop. The data is for =0. The relevant comparisons are between the product approximation and the actual blocking probability of the long flows; comparing the absolute blocking probabilities between the MBAC and the endpoint designs is misleading because the parameter values are not tuned to give equivalent loss rates.

2000

"... In PAGE 11: ... The question we have is whether endpoint admission control experiences more severe discrimination against multi-hop flows. Table6 shows the blocking probabilities for the two classes of flows. The MBAC blocking probability is well mod- eled by the product approximation.... ..."

Cited by 83

### Table 6: Blocking probabilities for the long (i.e., multi-hop) and short (i.e., single hop) flows: The blocking probabilities of the short flows at each of the three congested links are listed separately. The last column indicates the blocking probabilities that would result from assuming that the acceptance probability for a long flow is the product of the acceptance probabilities at each hop. The data is for = 0. The relevant comparisons are between the product approximation and the actual blocking probability of the long flows; comparing the absolute blocking probabilities between the MBAC and the endpoint designs is misleading because the parameter values are not tuned to give equivalent loss rates.

2000

"... In PAGE 11: ... The question we have is whether endpoint admission control experiences more severe discrimination against multi-hop flows. Table6 shows the blocking probabilities for the two classes of flows. The MBAC blocking probability is well mod- eled by the product approximation.... ..."

Cited by 83

### Table 6: Blocking probabilities for the long (i.e., multi-hop) and short (i.e., single hop) flows: The blocking probabilities of the short flows at each of the three congested links are listed separately. The last column indicates the blocking probabilities that would result from assuming that the acceptance probability for a long flow is the product of the acceptance probabilities at each hop. The data is for = 0. The relevant comparisons are between the product approximation and the actual blocking probability of the long flows; comparing the absolute blocking probabilities between the MBAC and the endpoint designs is misleading because the parameter values are not tuned to give equivalent loss rates.

2000

Cited by 83

### Table 6: Blocking probabilities for the long (i.e., multi-hop) and short (i.e., single hop) flows: The blocking probabilities of the short flows at each of the three congested links are listed separately. The last column indicates the blocking probabilities that would result from assuming that the acceptance probability for a long flow is the product of the acceptanceprobabilities at each hop. The data is for =0. The relevant comparisons are between the product approximation and the actual blocking probability of the long flows; comparing the absolute blocking probabilities between the MBAC and the endpoint designs is misleading because the parameter values are not tuned to give equivalent loss rates.

2000

Cited by 83

### Table 3. The measured values of the cone height and the cone base radius for the ten sample sets.

"... In PAGE 12: ... Then, Gaussian noise with mean = 0 and standard deviation = 3 is added to the nine pairs of stripe endpoints to simulate perturbation of the extracted stripe endpoints. The measured results of the cone height and base radius for the ten sets are given in Table3 . The mean of the ten estimates of the height was 114.... ..."