### Table 2. Summary of neural network proper- ties.

in Communicating Neural Network Knowledge between Agents in a Simulated Aerial Reconnaissance System

Cited by 1

### Table 2. Summary of neural network proper- ties.

in Communicating Neural Network Knowledge between Agents in a Simulated Aerial Reconnaissance System

Cited by 1

### Table 1 Examples of different forms of network ties: horizontal and vertical, formal and informal

### Table 3: Pearson Correlation between Network and Tie Characteristics with Frequency and Perceived Effectiveness of Email and Face-To-Face Contact

"... In PAGE 16: ... To enable comparisons across these different relational networks, we standardize indices by dividing the individual degree values by the maximum possible degree expressed as a percentage (Borgatti, 1999). RELATIONSHIPS AND NETWORKS IN TECHNET Range TechNet scholars report having an average of 5 friends within TechNet (22 percent of the total membership), 10 colleagues (43 percent), 9 acquaintances (39 percent), and are just aware of 4 others (17 percent; Table 1, see also Table3 below; Koku, et al., 2001).... In PAGE 20: ...TechNet scholars with large personal networks of collaborators and high (degree) centrality communicate more face-to-face and by email ( Table3 ).2 Scholars with high betweenness centrality have a similar pattern, except that they have appreciably more face-to-face contact with their collaborators.... In PAGE 20: ... Scholars with large collaborative and reading networks use more media to communicate, and are more likely to perceive email and face-to-face contact as effective for scholarly communication (see also Ahuja amp; Carley, 1999). lt; lt; lt; Table3 about here gt; gt; gt; The centrality of scholars in a network is significantly related to their communication behavior in four ways: 1. Scholars who reach out (have high out-degree) to other scholars for advice and discussing research tend to use several media (QAP r=0.... ..."

### Table 2. The probabilities of the functions of the 2-2-1 network of figure 2. These probabili- ties are based on the probabilities in table 1.

### Table 4. The probabilities of the functions of the 2-2-1 network of figure 2. These probabili- ties are based on the probabilities in table 1.

### TABLE 2 Summary of a Multilevel, Multitheoretical Framework to Test Hypotheses About Organizational Networks Null Hypothesis: All Ties Are Independent with Equal Probability

### Table 4. Variation in generalization and the mean error hessian measure for networks trained with the M1 and M2 roughness penal- ties on the link admission task.

"... In PAGE 4: ... However as in the previous problem we note that generalization ability does not remain constant, clearly a trade-off is taking place. This becomes more ap- parent in results tabulated for the M1 and M2 roughness penalties, see Table4 . By increasing the level of 1 and 2, and hence the balance in the reduction of the relative terms in the error function during learning, a monotonic re- duction in the mean error hessian measure is seen.... In PAGE 4: ... From the results it is clear that the level of generalization abil- ity passes through a minimum and then increases. This is particularly apparent in the M2 results in Table4 . At some point there will be an optimum level of complexity that the network can assume and this will match the required com- plexity needed to solve the problem.... ..."

### Table 3: The number of cases in which the P- Loc algorithm found larger/smaller probabili- ties than DWA* in network Andes when spend- ing a little bit more time than DWA*.

"... In PAGE 6: ... However, in practice the search time is not continuous in the number of search steps, so we just chose parameters for P-Loc such that it spent only a little bit more time than DWA*. Table3 shows the compar- ison results. We can see that after increasing the search steps of P-Loc, DWA* still main- tains better accuracy.... ..."

### Table 3: The number of cases in which the P- Loc algorithm found larger/smaller probabili- ties than DWA* in network Andes when spend- ing a little bit more time than DWA*.

"... In PAGE 6: ... However, in practice the search time is not continuous in the number of search steps, so we just chose parameters for P-Loc such that it spent only a little bit more time than DWA*. Table3 shows the compar- ison results. We can see that after increasing the search steps of P-Loc, DWA* still main- tains better accuracy.... ..."