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Table 1 Base non-adaptive processor.

in ARCHITECTURAL ADAPTATION FOR THERMAL CONTROL BY
by Jayanth C. Srinivasan
"... In PAGE 17: ...Methodology 5.1 Architectures The base non-adaptive processor studied is similar to the MIPS R10000 and is summarized in Table1 . We assume a centralized instruction window that integrates the issue queue and Reorder Buffer (ROB) with a separate physical register file.... ..."

Table 6. Parameters for Non-Adaptive Simulation

in An Adaptive Agent Based Economic Model
by Sonia Schulenburg, Peter Ross, South Bridge 2000
Cited by 9

Table 1. Base non-adaptive processor.

in The Importance of Heat-Sink Modeling for DTM and a Correction to “Predictive DTM for Multimedia Applications”£
by unknown authors

Table 3 How to Create Non-Adaptive Teams

in Adaptive Teams
by unknown authors
"... In PAGE 13: ... Even though teams may espouse the goal of being adaptive, they may be unwilling or unable to make the changes necessary. Table3 lists the practices that will make it difficult or impossible for a team to be adaptive. Table 3 can be treated as a primer of how to create teams that have the wrong stuff.... In PAGE 13: ... Table 3 lists the practices that will make it difficult or impossible for a team to be adaptive. Table3 can be treated as a primer of how to create teams that have the wrong stuff. Here is what you would do to create non-adaptive teams.... ..."

Table 7. Returns of Tt1 from Non-Adaptive Simulation

in An Adaptive Agent Based Economic Model
by Sonia Schulenburg, Peter Ross, South Bridge 2000
Cited by 9

TABLE III Example non-adaptive global diagnosis.

in Optimal interconnect diagnosis of wiring networks
by Weiping Shi, W. Kent Fuchs 1995
Cited by 9

Table 3: Slowdown relative to the non-adaptive version. The

in The Utility of Exploiting Idle Workstations for Parallel Computation
by Anurag Acharya, Guy Edjlali, Joel Saltz

Table 5: Results of CLAS and CAS (shortest first non adaptive branching rule)on the uf100 series: randomly generated phase transition 3-sat instances.

in CLAS: a Complete Learning Algorithm for Propositional Satisfiabilty
by Renato Bruni, Antoni Sassano

Table 12: Experimental results of non-adaptive GBGP with different grammars for the modified-n-parity problem. We perform another experiment to determine if the original grammar (Table 2) and the modified grammar (Table 8) have sufficient biases for generating correct recursive programs without crossover and mutation. In this experiment, 500,000,000 programs are created randomly and no correct recursive programs can be obtained for the two grammars. This experiment suggests that genetic operators are essential for this problem.

in Evolving recursive programs by using adaptive grammar based genetic programming
by Man Leung Wong, Tuen Mun 2005
Cited by 3

Table 3: The numbers of non-terminating programs generated by adaptive GBGP and non-adaptive GBGP.

in Applying Adaptive Grammar Based Genetic Programming in Evolving Recursive Programs
by unknown authors
"... In PAGE 6: ... In other words, adaptive GBGP can solve the even-7-parity problem about 94 times faster. Table3 summarizes the numbers of non-terminating programs generated by adaptive GBGP and non-adaptive GBGP in 100 trials. The average number of non- terminating programs generated by adaptive GBGP is 440.... ..."
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