"... In PAGE 10: ... All input ports not connected to bers were connected to laser arrays for originating lightpaths, while all free output ports were connected to receiver arrays for terminating lightpaths. Table1 provides statistics on the maximum number of single-hop connections that may be set up for physical network topologies of di erent sizes. This study and its results might be desirable if the required virtual topology is not known apriori; thus, the objective is to maximize the number of single-hop connections assuming an all-to-all tra c, i.... In PAGE 10: ... Then we repeated these experiments for network sizes be- tween 50 and 100 nodes. Results in Table1 demonstrate that this architecture is scalable15 and the maximum number of lightpaths in the network grows linearly with the number of nodes in the network. For a given network size, Table 1 provides the mean number of total connections achievable in the network.... In PAGE 10: ... Results in Table 1 demonstrate that this architecture is scalable15 and the maximum number of lightpaths in the network grows linearly with the number of nodes in the network. For a given network size, Table1 provides the mean number of total connections achievable in the network. The results are averaged over 500 topologies which were randomly generated.... ..."

"... In PAGE 10: ... All input ports not connected to bers were connected to laser arrays for originating lightpaths, while all free output ports were connected to receiver arrays for terminating lightpaths. Table1 provides statistics on the maximum number of single-hop connections that may be set up for physical network topologies of di erent sizes. This study and its results might be desirable if the required virtual topology is not known apriori; thus, the objective is to maximize the number of single-hop connections assuming an all-to-all tra c, i.... In PAGE 10: ... Then we repeated these experiments for network sizes be- tween 50 and 100 nodes. Results in Table1 demonstrate that this architecture is scalable15 and the maximum number of lightpaths in the network grows linearly with the number of nodes in the network. For a given network size, Table 1 provides the mean number of total connections achievable in the network.... In PAGE 10: ... Results in Table 1 demonstrate that this architecture is scalable15 and the maximum number of lightpaths in the network grows linearly with the number of nodes in the network. For a given network size, Table1 provides the mean number of total connections achievable in the network. The results are averaged over 500 topologies which were randomly generated.... ..."

"... In PAGE 21: ... Table1 shows the average link utilization during the measurement interval when the number of connections is 8. By inspecting the link utilization over the whole network, we can see that the LBR protocols distribute the data messages more uniformly over the whole network than DVR and LSR.... ..."

"... In PAGE 12: ... LBR_FR has the highest throughput when the number of connections is in the range from 1 to 5, while LBR_BR2 has the highest throughput when the number of connections is more than 5. Table1 shows the average link utilization during the measurement interval when the number of connections is 8. By inspecting the link utilization over the whole network, we can see that the LBR protocols distribute the data messages more uniformly over the whole network than DVR and LSR.... ..."

"... In PAGE 6: ... Table1 : Link Utilization: (Measurement interval: 50,000 msec, Number of Connections: 7) 8 FUTURE WORK We have many possible directions for future work. The routing protocol proposed here is based on flat network architectures.... ..."

"... In PAGE 8: ....2. Results and analyses Our analysis of these semantic networks focuses on five properties: sparsity, connectedness, short path-lengths, high neighborhood clustering, and power-law degree distributions. The statistics related to these properties are shown in Table2 (under the Data columns), and the estimated degree distributions for each network are plotted in Figure 5. To provide a benchmark for small-world analyses, we also computed the average shortest-path lengths (Lrandom) ... In PAGE 10: ...01 and 3.19 (see Table2 ). The high-connectivity words at the tail of the power-law distribution can be thought of as the hubs of the semantic network.... In PAGE 13: ... Incorporating additional processes would surely make the model more realistic but would also entail adding in more free parameters, corresponding to the relative weights of those mechanisms. Given that the data we wish to account for consists of only the few summary statistics in Table2 and the degree distributions in Figure 5, it is essential to keep the number of free parameters to an absolute minimum. Our model for undirected networks (model A) has no free numerical parameters, while our model for directed networks (model B) has just one free parameter.... In PAGE 16: ...95, corresponding to the reasonable assumption that on average, 19 out of 20 new directed connections point from a new node towards an existing node. We evaluated the models by calculating the same statistical properties (see Table2 ) and degree distributions (see Figure 5) discussed above for the real semantic networks. Because the growing models are stochastic, results vary from simulation to simulation.... ..."

"... In PAGE 59: ... Of course, a patient with progressive dementia may also have some amount of deteriorationwithinthe phonologicalpathway itself. As Figure20 and Table9 illustrate, such impairment would tend to degrade performance on exception words even further, but also would affect performance on regular words and nonwords to some degree. One final comment with respect to phonological dyslexia seems appropriate.... In PAGE 59: ... In the current simulation, the external input to the phoneme units that represents the contributionof the semantic pathway is sufficient,on its own,to support accurate word reading (but not nonword reading). On the other hand, severe damage to the phonological pathway certainly impairs nonword reading (see Figure 20 and Table9 ). In the limit of a complete lesion between orthography and phonology, nonword reading would be impossible.... ..."

"... In PAGE 5: ... 4 Results Typically, with every tness function the tness converged within 250 evalua- tions (we continued the experiments up to 1000 evaluations). The neural-network weights evolved in the best controller are shown in Table1 . In the table the rst two rows show the bias node (b) and the IR-sensors (0 to 7) and the values of the corresponding connective weights to the left motor (w * ML).... ..."

"... In PAGE 15: ... His reading disorder was quite severe initially, and he also showed an advantage for abstract words in auditory word/picture matching, suggesting modality-independent damage at the semantic level. Table2 illustrates the double dissociation of concrete and abstract word reading produced after direct versus clean- up lesions to the network. The results listed are the averages from 50 instances of each type of lesion.... In PAGE 16: ...types were chosen because, among the locations and severities of lesions investigated by Plaut and Shallice, these two produce the clearest double dissociation between correct performance on concrete versus abstract words (as shown in Table2 ). Notice that the two lesion types are not equated for the overall level of performance that they produce (average percent correct is 40.... ..."