### Table 8: Best Predictor, Simplified Form

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### Table 3. Computational results for test problems.

"... In PAGE 11: ... Better programs required fewer generations and less computation time. Table3 compares the new encoding method, the penalty encoding method and in- teger programming for the test problems. The left half of Table 3 (a) shows the computa- tional results for the new encoding method and the right half presents for the penalty en- coding method.... In PAGE 11: ... Table 3 compares the new encoding method, the penalty encoding method and in- teger programming for the test problems. The left half of Table3 (a) shows the computa- tional results for the new encoding method and the right half presents for the penalty en- coding method. #8 means that the number of plants is eight, and so on.... In PAGE 11: ... The last three rows show the goal value of the prob- lem, the generation and the time cost in which the goal is attained. Table3 (b) displays the results from using integer programming. According to the schema theorem and the ... In PAGE 12: ... The goal solutions can be thought of as sufficiently good solutions. Table3 shows that the new method requires fewer generations and computation time to produce goal solutions. Table 3 enables the trend line for the number of genera- tions required by the genetic algorithm to be drawn, versus the number of plants.... In PAGE 12: ... Table 3 shows that the new method requires fewer generations and computation time to produce goal solutions. Table3 enables the trend line for the number of genera- tions required by the genetic algorithm to be drawn, versus the number of plants. The gradient of Fig.... In PAGE 13: ... The LINGO package was used to solve these test problems by integer programming. For these cases, LINGO can get feasible solutions only ( Table3 (b)) because the test problems are all highly complex. The com- putational results of this section demonstrate that the new encoding method improves the performance of genetic algorithms by reducing their search space.... ..."

### TABLE B1 Particular Forms of Fundamental Matrices # p Simplified form of fundamental matrices For example generated by: n

2000

### Table 2.1. Simplified Form of Locking Behavior for Aries/KVL

"... In PAGE 6: ...hat of Table 2.1. One of the reasons for this is that it handles the situation where the index being locked is non-unique in a more efficient manner. Although the protocol of Table2 would work for non-unique indexes, the fact that an Insert requires an X lock on the keyvalue of the entry being Inserted means that two entries with the same keyvalue could not be inserted concurrently by different transactions. In the full Aries/KVL locking protocol, Inserts often acquire IX locks on the keyvalue inserted, making the overall protocol more complex.... ..."

### Table 1. Potential Heuristics. The Heuristic column presents the simplified forms of the theory. The Relevant column indicates the total number of visualizations for which the heuristic was pertinent.

2006

"... In PAGE 11: ... Analysis using these theories can be considered as a form of heuristic evaluation.13,35 We summarize a subset of the applied theory, in the form of possible heuristics, in Table1 . These heuristics are over simplifications, but the application of them may raise important issues.... ..."

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### TABLE 4: Estimated individual Bayesian probabilities P( Tj= Mi) for the first 3000 frames Star Wars MPEG stream, determined using the simplified form of Bayes theorem. Tj

### Table 6.1: Cost (literals in factored form) of Berkeley SIS Simplify vs. CYCLIFY for Espresso Benchmarks.

2004

### Table 6.2: Cost (literals in factored form) of Berkeley SIS Simplify vs. CYCLIFY for the Workshop on Logic and Synthesis Benchmarks.

2004

### Table 7. Simplified BY DC values.

2001

"... In PAGE 13: ... Table 6 shows the measured values for the checkpointing scheme dependent parameters listed above. By applying each parameter value in Table 5 and 6, we derived more simplified forms of analytic models as in Table7 . CA D4 and CA CQ in the equations of Table 7 are application dependent parameters.... In PAGE 13: ... By applying each parameter value in Table 5 and 6, we derived more simplified forms of analytic models as in Table 7. CA D4 and CA CQ in the equations of Table7 are application dependent parameters. We used the CA D4 and CA CQ values measured in [14].... In PAGE 14: ... B. Measured first checkpointing overhead : BY DC BD Each of the equations in the left column of Table7 corresponds to the first checkpoint for each scheme. Only C6 CQ affects the checkpointing overhead, that is, the overhead of the first checkpoint is application independent.... In PAGE 14: ... C. Measured subsequent checkpointing overhead : BY DC D2 BN B4D2 AL BEB5 By applying the measured values in Table 8 to the equations in the right column of Table7 , we derived the checkpointing overheads of each application analytically. Figure 4 shows BY DC D2 BN B4D2 AL BEB5 values, the normalized overhead of checkpointing, for each application.... ..."

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### Table 6.3: Cost improvement (literals in factored form) of CYCLIFY over Berkeley SIS Simplify for randomly generated networks (25 trials per row).

2004