### Table 1. Change in topological parameters for various ways of increasing network size from n to n2. For example, an entry of D for diameter means that there is no change when the network size is squared and 2D means that the diameter is doubled. Squared network refers to the cross product of a network with itself.

"... In PAGE 5: ... In particular, we showed that swapped networks are cost-effective, modular, packageable, and quite robust. Table1 indicates how the main topological parameters of certain classes of interconnection networks change as the network size is scaled from n to n2. The various parameters are formulated in terms of the respective parameters for the network of size n.... In PAGE 5: ... The various parameters are formulated in terms of the respective parameters for the network of size n. As evident from Table1 , swapped networks offer a mechanism for increasing the size of a network with relatively small cost increase, while limiting the deterioration of topological parameters and ensuring strong fault tolerance. Work in progress includes expanding our results on the properties of swapped network to include other topological attributes as well as a deeper analysis of their performance parameters and robustness attributes.... ..."

### Table 7 Instantiation of a Complex Conceptual Network Knowledge Structure

"... In PAGE 13: ... However, each of these classes share the same value, plants , on property 2, Source of Food . By sorting on the second property we can identify a new set of coordinate concepts as in Table7 . Note in this case that the first property discriminates on the second set of coordinate concepts while the second property discriminates on the first level of coordinate concepts.... ..."

### Table 1. Principal Substance of a Network

"... In PAGE 19: ... Since the structure of a given policy network is analysed through specific measures of various structural properties, visualization should make these properties visible. In order to better understand the possibilities and limitations of graphical design to convey the relevant information, typical policy network substance is grouped into two main categories with four subcategories each (see Table1 ). These distinctions serve as a guideline for how visualization can enhance the understanding of complex multi-dimen- sional settings by separating different kinds of information.... In PAGE 20: ...Table1 correspond to the three levels of interest: actor, group, and network.17 In policy network analysis, one is often interested in all three levels of aggregation simultane- ously in order to explore or communicate properties in their context.... ..."

### Table 5 is an instantiation of a more complex concept network. Note that the first

"... In PAGE 7: ... Table5 Instantiation of a More Complex Concept Network. Processes and Activities A process is knowledge about how something works.... In PAGE 13: ...Page 13 Generalization Table5 and Table 7 illustrate a more complex knowledge structure that enables a learner to make generalizations. A generalization is when classes from different set of coordinate concepts are seen as coordinate concepts for a new set of coordinate concepts.... In PAGE 13: ... A generalization is when classes from different set of coordinate concepts are seen as coordinate concepts for a new set of coordinate concepts. In Table5 finches, ants, and cows each appear in a different coordinate set corresponding to birds, insects, and mammals. However, each of these classes share the same value, plants , on property 2, Source of Food .... ..."

### Table 2: Summary of key properties of the test networks. Some other (non-road) graphs of similar sizes are shown for comparison. The number of circuits is an interesting measure of graph complexity for instance.

"... In PAGE 3: ... We do not consider this reachability index for our bi-directional trunk road networks however. Table2 summarises these static graph metrics for other road network data sets and some other graphs. It is also possible to do a sensitivity or perturbation analysis using these metrics.... In PAGE 4: ... In general we are severely limited in use of the algorithm for counting or enumerating the elementary circuits due to its intractability for anything but small networks of around 60 vertices and mean degree of around 6. 4 Model Network Results Table2 summarises the static properties of the road networks we analyse in this paper along with some other simple graphs of similar size for comparison. It is worth drawing attention to the simple lattice networks generated for comparisons.... ..."

### Table 2. Properties of Interconnection Networks

1994

"... In PAGE 12: ... However, total hypercube wiring complexity grows super linearly with the number of processors and the likelihood increases that most wires are unused most of the time. Table2 compares several simple topologies as a function of processor number P from the point of view of amount of wiring (difficulty of building), connectivity (ease of programming) and maximal... In PAGE 16: ...1. Hypercube Architectures Hypercube architectures have been very frequently developed because of the advantages of high connectivity and low wiring costs already referred to above in Table2 . Mathematically, a hypercube may be easily defined recursively, as a set of vertices and edges, as follows.... ..."

Cited by 23

### Table 2. Structural properties of the networks evolved by the different crossover op- erators for the ALARM benchmark (averaged for 10 runs).

2002

"... In PAGE 7: ... The structural properties of the evolved BNs are consistent with the analysis above. Table2 shows the total number of parameters (g) as well as the BIC measure discussed earlier. It can be seen that the networks provided by AT and PheAT are slightly more complex on average than those produced by GT and PheGT, whereas all of them tend to be simpler than the true network.... ..."

Cited by 8

### Table 2. Structural properties of the networks evolved by the different crossover op- erators for the ALARM benchmark (averaged for 10 runs).

2002

"... In PAGE 7: ... The structural properties of the evolved BNs are consistent with the analysis above. Table2 shows the total number of parameters (g) as well as the BIC measure discussed earlier. It can be seen that the networks provided by AT and PheAT are slightly more complex on average than those produced by GT and PheGT, whereas all of them tend to be simpler than the true network.... ..."

Cited by 8

### Table 5 Instantiation of a More Complex Concept Network.

"... In PAGE 7: ...Page 7 Table5 is an instantiation of a more complex concept network. Note that the first property distinguishes among the first level of coordinate concepts: birds, insects, and mammals.... In PAGE 13: ...Page 13 Generalization Table5 and Table 7 illustrate a more complex knowledge structure that enables a learner to make generalizations. A generalization is when classes from different set of coordinate concepts are seen as coordinate concepts for a new set of coordinate concepts.... In PAGE 13: ... A generalization is when classes from different set of coordinate concepts are seen as coordinate concepts for a new set of coordinate concepts. In Table5 finches, ants, and cows each appear in a different coordinate set corresponding to birds, insects, and mammals. However, each of these classes share the same value, plants , on property 2, Source of Food .... ..."

### Table 3 How has the membership changed since the network was established? Response: Number of networks

2006

"... In PAGE 6: ...able 2 How many businesses or individuals belong to the network?............. 11 Table3 How has the membership changed since the network was established?.... ..."