### Table 1: Symbol table

1998

"... In PAGE 5: ... After, we give the proposed solution, for d = 2 dimensions and for arbitrary d. Table1 gives a list of symbols used throughout this section. 3.... ..."

Cited by 8

### Table 1: Optimal convergence rates c 2 (0; 1) and noncentrality parameters gt; 0 of the (1+1)-EA for Cauchy, Student, and Gaussian distribution for ` = 3. The maximum convergence velocity increases (since c decreases) from Cauchy via Student to Gaussian mutations. After the analysis of the low-dimensional case one may inquire in the scaling behavior of the convergence rates if the dimension ` becomes large. Since solving the integral in (10) seems intractable for arbitrary `, the subsequent analysis will be con ned to asymptotic convergence rates (` 1).

1997

Cited by 14

### Table 1. Cubature rule pairs

"... In PAGE 5: ... However, only a few classes of rules are known that can be constructed for an arbitrary dimension s. In Table1 we list the cubature rules used in our experiments, together with the degree of the rule and the growth-rate of the number of abscissas n0 depending on the dimension s. The column labeled Q(1) gives a literature reference for the primary rule, which is used for estimating the integral.... ..."

### Table 4.5 Change in Average Lateral Dimension for RSST-CH Specimens During Testing, HVS Mix.

1999

Cited by 1

### Table 2 shows that, although the process which cuts the squares along the antidiago- nal (see Section 2.3) gives a very high value of 1 (and thus 1 ? 2) for the modi cation A0 of algorithm A, the approximation exponents are on the whole not as good as those of the algorithms in Table 1.

1996

"... In PAGE 7: ... The numerical experiments described in Section 5 (cf. Table2 ) seem to indicate that the subsquare procedure is preferable. At rst sight the generalization of algorithm A to arbitrary dimension d seems quite straightforward: consider the ray in Rd+1 and the d-dimensional hyperplanes Pi, i = 1; : : : ; d + 1, and divide the d-dimensional hypercube into 2d sub-hypercubes.... In PAGE 16: ... Table2 (Division along antidiagonal instead of subsquare selection)... ..."

Cited by 3

### Table 14: Design instances with duplicate elements in the cost column

2004

"... In PAGE 7: ...able 13: List of dimensions from satellite test problem ........................................................................... 106 Table14 : Design instances with duplicate elements in the cost column.... ..."

Cited by 6

### Table 2: Expected execution times (arbitrary units).

1999

"... In PAGE 13: ... Consider the performance of the heuristics for a very simple case of three tasks t0, t1, and t2 arriving in that order. Table2 shows the expected execution times of tasks on the machines in the system. All time values in the discussion below are the expected values.... ..."

Cited by 78

### Table 3: Task set with arbitrary processing times.

1994

"... In PAGE 5: ... This algorithm compacts the schedule S generated in Step 4 of Algorithm H. The example in Table3 and Figure 8 illustrates Algo- rithm H. T3 has the longest processing time on P1, T1 on P2, T4 on P3, and T3 on P4.... ..."

Cited by 61