### Table 1. RLS Heuristic Performance for Infinite Planning Horizon Case (*) System A System B System C

"... In PAGE 13: ... The RLS heuristic performance is analyzed by comparison with the optimum solution as found by the DP algorithm of Crowston, Wagner and Williams [9]. Table1 tabulates the minimum, average and maximum percent deviations from the optimum solutions among the 10 RLS heuristic replications for each problem instance. The entries in Table show that with the exception of one or two instances, even the worst of the 10 runs was substantially less than 1% away from the optimum solution for all 30 problems considered.... In PAGE 21: ...List of Tables Table1 . RLS Heuristic Performance for Infinite Planning Horizon Case Table 2.... ..."

### Table 4: Miss rates for the baseline architecture (no prefetching) and infinite SLCs.

1995

"... In PAGE 12: ...version 2.1) with optimization O2. For all measurements, we gather statistics during the parallel sections only according to the recommendations in the SPLASH report [18]. Table4 shows the cold, coherence, and total cache read miss rates for each of the applications for the baseline architecture without prefetching and with infinite SLCs. Since we assume full inclusion between the FLC and the SLC, the miss rates is calculated as the total number of read misses in the SLCs divided by the total number of read accesses to shared data in the system.... ..."

Cited by 47

### Table 4: Running times for certain multihomogeneous systems with xed n = 4 and varying polytope vertex cardinality m.

"... In PAGE 14: ... We see that in this small sample the behaviour of the practical complexity is indeed exponential in n and grows at a rate bounded by that of the asymptotic bound we have derived. Table4 considers the running times of the multihomogeneous systems examined above, as an additional test of the assumptions used in deriving the asymptotic bounds. The bound of proposition 6.... ..."

### Table 3. The processing time for each fish with dynamic sim- ulation and with synthetic motion capture on an SGI R10000 InfiniteReality workstation

"... In PAGE 12: ... The speed up over the original biomechanical anima- tion is due to the accelerated motor system and the efficient graphical display model. Table3 compares for a single fish the computation times required for the original biomechanical model and our synthetic motion capture model. The indicated times are for the case when the fish is fully visible, which includes the reconstruction of the body-coordinate system and positions of all the nodal points.... ..."

### Table 3: Temporal infinite sequential product of spacial infinite parallel processes.

### TABLE I Comparison of some self-replicating structures in cellular space models. Models shown include variations of cellular automata: CT-machines are programmable finite automata with registers, -Universes are CAs augmented with chemistry-like operators, non-uniform CAs allow cells to have differing rules, and W-machines are Turing machine models that are programmable using high-level instructions.

1997

Cited by 18

### TABLE I Comparison of some self-replicating structures in cellular space models. Models shown include variations of cellular automata: CT-machines are programmable finite automata with registers, -Universes are CAs augmented with chemistry-like operators, non-uniform CAs allow cells to have differing rules, and W-machines are Turing machine models that are programmable using high-level instructions.

1997

Cited by 18

### Table 1. Attributes for Handover Initiation For handover decision, the aim of the simulation is to demonstrate that by changing certain inputs into the system, the choice of the selected segment will vary.

### Table 1: There are at least 29 = 512 different possibilities to build up an exploration system even when ignoring the continuity of certain criteria.

in Tutored by:

2004