### Table 2 Optimal streams of consumption, and optimal patterns of contributions, fractions of account balance in stock invest- ment, and accumulative savings in both accounts for the savings allocation problem

1998

"... In PAGE 7: ... We go forward from the current period 0, starting with X0 quot; gt;0 quot;0, and use bilinear interpolation in each period successively to get the approximate solutions of those decision variables. We report in Table2 these optimal streams of consumption S.... In PAGE 9: ... To compare the numerical performance and verify the accuracy of the results solved by dynamic programming with bivariate shape-preserving interpolation, we redo this stochastic optimization problem by using only the NPSOL subroutines to solve the corresponding non-linear program. We report the decision variable outputs in the corresponding parentheses in Table2 . Note that the minor di!erences indicate the dynamic programming scheme with shape-preserving smooth approximation methods can do as well as NPSOL in solving the pension savings allocation problem.... ..."

### Table 1. Study of the horizontal position accuracy Ga7G20 Shape preservation can be studied at the operator level, where the average shape change values for different algorithms are compared or at the algorithm level, where the average shape change values for groups of lines of different complexity are compared. The creation of graphs and tables with the items shown in Table 2 is proposed. In addition, the construction of a table showing the clustering results (hierarchical and non-hierarchical) of different generalization schemas (different algorithms and a range of tolerance values) and the comparison with the initial segments clustering is considered useful.

"... In PAGE 7: ...7 Ga7G20 Horizontal position accuracy can be studied at the operator level, where the average horizontal position error values for different algorithms are compared or at the algorithm level, where the average horizontal position error values for groups of lines of different complexity are compared. The creation of graphs and tables with the items shown in Table1 is proposed (Table 1). Study Level Item 1 Item 2 1.... ..."

### Table 1. Benchmark results for verifying shape preservation. We show the analysis time, the maximum number of disjuncts at any program point (Disj.), and the maximum number of iterations at any point (Iter.). Where applicable, we also show the analysis time for the analogous operation in the structure without back pointers.

### Table 1. Parameter settings for MEBAA interpolation algorithm.

2004

"... In PAGE 14: ... Options to find a specified number of points in each quadrant and to use all data points are not used. Settings used in the MEBAA interpolation are shown in Table1 , below. A minimum of six scatter data points is used to determine the elevation for each interpolant.... In PAGE 15: ... region, whose size is described below in Table1 , is searched in succession. If at least six scattered data points are located inside a bounding region, the search stops and all located ... ..."

### Table 2. Aerosol Optical Properties at 0.4 mm Wavelength (RH = 70%)a

2003

"... In PAGE 2: ... [2002] for other aerosols, and apply it to local RH from the GEOS fields. Table 1 shows the hygro- scopic growth factors and Table2 shows the effective radius re at 70% humidity. The effective radius is defined as Rr pr3f(r)dr/Rrpr2f(r)dr, where f(r) is the fraction of par- ACH 6 - 2... In PAGE 3: ...f Wild et al. [2000]. We tabulate the optical properties at the RH values in Table 1, and interpolate in the simulation. Table2 shows the resulting optical properties at 0.4 mm and 70% RH.... ..."

Cited by 27

### Table C.2: Equivalent Physical Time Constants [s] D Gain Scheduling Schemes In principle, there are two approaches to control design for systems which exhibit signi- cant changes in dynamics across their operating envelope. One possibility is to consider local representations of such a system and to design controllers for individual operating points. The functionality of the controllers is then to be integrated to cover the entire operating envelope by interpolation. In doing so, it is important to ensure that the data to be interpolated are su ciently smooth and that the states of the di erent controllers are always consistent with the state of the system.

### Table 1. Statistics including the vertex number, the running time, and the Hausdorff distance [19] for the examples shown in the paper.

"... In PAGE 10: ...ig.6. Morphing sequence between dinosaur and horse models. Table1 shows the statistics for the examples shown in the paper, including the vertex number, the running time, and the Hausdorff distance [19] (with respect to the size of bounding box). As we can see, our approach achieves a good combination of speed, mesh quality, and shape preservation.... ..."

### Table 2. RESULTS: Interpolant elevations for each algorithm at each Point.

2004

"... In PAGE 16: ...igure 6. Point 1 area map, point 1 is circled. Scattered data points are shown in blue. All four interpolation algorithms are applied to both the completed data set and the reduced data set. Resulting interpolant elevation for all points for all interpolation methods are shown in Table2 . Point 2 best illustrates the utility of the MEBAA algorithm for areas of scarce data, as illustrated in Figure 8.... In PAGE 18: ... Figure 10 shows Point 4 and all of the data points that are removed from the second scatter set. Table2 contains the resulting elevation at each point as interpolated by each algorithm. Point 1 shows that all interpolation algorithms do an adequate job of assigning a reasonable elevation in areas with adequate scatter data.... ..."

### Table 4: The LU factorization on the e cient 8 63 grid shape, with various data locality choices. Performance degrades with the deviation from scatter-scatter distribution, but by not more than a factor of two in the worst case.

"... In PAGE 24: ... We also see that using less nodes (last three lines utilize 256 nodes) achieves higher e ective per-node performance, but longer overall runtime. Table4 . Size = 10000x10000, 8x63 shape... ..."