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Table 5: Soundness and completeness for column mapping decisions.
2001
"... In PAGE 12: ... 5.3 Results Table5 shows the soundness and completeness for the four types of decisions made by Autoplex. A perfect sequence of decisions would result in Soundness =... In PAGE 13: ... Furthermore, optional columns that are not mapped do not cause a false negative for table mapping. Table5 also shows the performance for tuple selection is slightly better than the performance for tuple partitioning. This improvement is due to the pruning strategy employed by the J48 classi#0Ccation tree algorithm that learns selection predicates.... ..."
Cited by 27
Table 1 : Mapping decision theory and CSP theory
Table 1. Decision map example. The axis information relates to the decision maps in Figure 1.
2006
"... In PAGE 2: ... 3 Quadtrees and MPI collective operations We use the collective algorithm performance information on a particular system to extract the information about the optimal methods and construct a decision map for the collective on that system. An example of a decision map is displayed in Table1... ..."
Cited by 2
Table 1. Decision map example. The axis information relates to the decision maps in Figure 1.
2006
"... In PAGE 2: ...Table1... ..."
Cited by 2
Table 1. Behavior-PE mapping decisions and the produced variable identification for be- havior example 1.
1995
"... In PAGE 12: ... For the same behav- ior specification, the behavior-PE mapping decision deter- mines the variable identification. For example, as shown in Table1 , if different behavior-PE mapping decisions are made for the behavior specification described in Figure 5, then the variables v1 and v2 have different identifications. If we map the behavior AC to PE1 as shown in the raw 1 of Table 1, then v1 and v2 become the local variables of PE1.... In PAGE 12: ... For example, as shown in Table 1, if different behavior-PE mapping decisions are made for the behavior specification described in Figure 5, then the variables v1 and v2 have different identifications. If we map the behavior AC to PE1 as shown in the raw 1 of Table1 , then v1 and v2 become the local variables of PE1. However, if we map behavior AB to PE1 and map behav- ior C to PE2 as shown in the raw 2 of Table 1, then variable v1 becomes the local variable of PE1 and v2 becomes the global variable.... In PAGE 12: ... If we map the behavior AC to PE1 as shown in the raw 1 of Table 1, then v1 and v2 become the local variables of PE1. However, if we map behavior AB to PE1 and map behav- ior C to PE2 as shown in the raw 2 of Table1 , then variable v1 becomes the local variable of PE1 and v2 becomes the global variable. This is because that v2 is connected to both behavior AB and behavior C, which are mapped to differ-... In PAGE 33: ...308kB Table 11. Required memory sizes of PEs in HW-SW co-design of Vocoder project in Table1 0, we reduce the required memory size of Cold- Fire by 28% when we analyze the lifetime of behavior vari- ables and allow behavior variables with un-overlapped life- time to share the same memory portion. 8.... ..."
Table 4: Classification accuracy of simulated examinations using MAP decision theory and IRT scoring by item bank, test size and underlying ability distribution. uniform normal
"... In PAGE 20: ... For each test, 1,000 examinees and their item responses were simulated. The results for select test sizes with the CSAP are shown in Table4 and all CSAP values are plotted in Figure 1. There is virtually no difference between the accuracies of decision theory scoring and IRT scoring with either the uniform or normal underlying ability distributions.... ..."
Cited by 1
Table 2. Table enumerating the broad categories of resources, their use in worklist choice decisions and appropriately mapped visualisations.
"... In PAGE 9: ... So the general rules are able to be modi ed but can still be encapsulated in the development of a set of visualisation tools. Table2 maps each resource type to an appropriate visualisation. The table is by no means exhaustive, and is only limited by the number of application areas intended for the visualisations.... ..."
Table 2. Table enumerating the broad categories of resources, their use in worklist choice decisions and appropriately mapped visualisations.
"... In PAGE 8: ... So the general rules are able to be modi ed but can still be encapsulated in the development of a set of visualisation tools. Table2 maps each resource type to an appropriate visualisation. The table is by no means exhaustive, and is only limited by the number of application areas intended for the visualisations.... ..."
Table 3: Bivariate Probit Analysis of Decision to Buy Detailed Map and Respond to Threat with Action (simultaneous estimations)1
2004
"... In PAGE 17: ... THREAT LEVEL at location YELLOW ORANGE RED Detailed map: buy not buy not buy not Response: Marginal Totals Do nothing 10 44 1 42 0 8 105 Be more alert 24 77 60 62 4 8 135 Stay at home, await news 4 9 15 39 8 14 89 Evacuate 2 15 12 28 23 6 86 Marginal Totals 40 145 78 171 35 36 515 As discussed above, a bivariate probit model was chosen to model the decision to purchase the detailed map and to choose a response to the threat. The results of this estimation appear in Table3 . There are two basic specifications of the bivariate probit model: one named Cluster, the other No Cluster.... In PAGE 19: ...the two equations, but rather to unobserved factors for which variables were not available. Columns (2) and (4) of Table3 shows estimates of a Bivariate Probit model for the two decisions estimated simultaneously using full information maximum likelihood. Columns (1) and (3) show the same model specification with correction for the panel nature of the data gathering process.... ..."
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