### Table 2. Parameters for an NS surface.

"... In PAGE 7: ... Therefore, we adopt a relatively simple model: we assume that the surface is symmetric (in B and T) about the magnetic equator and divide the hemisphere into four magnetic latitudinal regions. We generate atmosphere models for each region with the parameters given in Table2 (note that the magnetic field distribution is roughly dipolar and Theta1B is the angle between the magnetic field and the sur- face normal). Using an analogous formalism to that described in Pechenick, Ftaclas amp; Cohen (1983) and Pavlov amp; Zavlin (2000), we calculate phase-resolved spectra and light curves from the whole NS surface (we assume M = 1.... ..."

### Table 5 gives maximum standard errors and maximum relative standard errors for the mean, variance, and probability surfaces produced by the kriging method and Monte Carlo Bioplume II. For the Bioplume II surfaces, these quantities were only computed for the centers of the grid cells. For the kriging surfaces, these quantities were computed over the entire 65 by 25 grid. The maximum relative standard errors of both methods compare quite well for all three surfaces. The maximum standard errors compare well for the mean and probability surfaces, but the maximum standard error for the variance surface is much higher for the kriging method. The largest standard errors for the variance were obtained between observation points in the area directly upgradient from the source, which is not modeled particularly well by the kriging method. All standard errors would be reduced by increasing the number of Monte Carlo trials used to generate the surfaces. Surface Max. SE Max. Relative SE

in Estimation of Contaminant Concentration in Ground Water Using a Stochastic Flow and Transport Model

### Table 5: Second Experiment: Results of hypothesis generation. Stage Surface T for Optimal Fork Matched Forks

2000

"... In PAGE 39: ... The matching process consists of four stages. Hypothesis-generation results for all stages are summarized in Table5 . Notice that, thanks to our indexing strategy, the number of scene/model fork matches is kept at a very minimal level, even for occluded surfaces.... In PAGE 39: ... Running the direct-match-based system (described in Section 8.1), we have found that the number of generated hypotheses increases from 46 (4, 8, 8 and 26, for the four stages, respectively, see Table5 ) to 761. Furthermore, clustering involves 245436 comparisons,... ..."

Cited by 2

### Table 3: First Experiment: Results of hypothesis generation. Stage Surface T for Optimal Fork Matched Forks

2000

"... In PAGE 33: ...2. Results of this process are summarized in Table3 . From this table, we observe that indexing is highly selective: on the average, less than 4% of the model forks... In PAGE 38: ... The later is imple- mented by modifying our system such that: 1) all surfaces are matched in a single stage, and 2) indexing is performed assuming surfaces are occluded and all edge ends are false. Running the modi ed system, we have found that the number of generated hypotheses increases from 93 (6 and 87, for the two stages, respectively, see Table3 ) to 422. Furthermore, clustering involves 71688 comparisons, compared to only 2889 in our system (for both stages).... ..."

Cited by 2

### Table 1. Comparison of HotSpot model and DELPHI model for the DELPHI BGA bench- mark chip under the same set of boundary conditions. Temperatures are in Celcius and with respect to ambient temperature.

2004

"... In PAGE 4: ... 4. The temperature readings from both models are listed in Table1 . The heat generated at the die surface is 2.... ..."

Cited by 2

### Table 1: Smooth Molecular Surface Generation Times

1994

"... In PAGE 5: ... 5 Results Our implementation has been done on Pixel-Planes 5#5B8#5D,although it is general enough to be easily portable to any other parallel architecture. Table1 shows our tim- ings for computation and display of the molecular surface for various molecules for a probe-radius of 1:4 #17 A. For these results we were using con#0Cgurations of 8, 16, or 24 Intel i860 processors.... In PAGE 5: ...ent as they are not a part of the DHFR molecule per se. At present, we are representing the molecular surface by trian- gles, and the column Tris in Table1 refers to the complex- ity of the computed surface in terms of number of triangles #28rounded to the nearest thousand#29. As can be seen, the value of k, the average number of neighbors, is fairly constant for a given probe-radius over... ..."

Cited by 3

### Table 1: Smooth Molecular Surface Generation Times

1993

"... In PAGE 8: ...Results Our implementation has been done on Pixel-Planes 5 #5B11#5D, although it is general enough to be easily portable to any other parallel architecture. Table1 shows our timings for computation and display of the molecular surface for various molecules for a probe-radius of 1:4 #17 A.For these results wewere using either a con#0Cguration of 13 or 26 Intel i860 graphics processors as shown below.... ..."

Cited by 8

### Table 1 presents RAM memory usage and computational time measurements for simultaneous generating and polygonizing vari- ous point set models. Note that our method is quite fast. Our exper- iments with state-of-the-art RBF-based 3D surface reconstruction techniques such as FastRBF [Carr et al. 2001] and others suggest that the MPU method is considerably faster than these other tech- niques. 2

"... In PAGE 7: ...6GHz Mobile Pentium 4 with 1GB RAM, and timings are listed as minutes:seconds. 2 Comparing the results of Table1 with those of Table 2 in [Carr et al. 2001] one can find that the MPU method is 20-30 times faster than the FastRBF technique [Carr et al.... ..."

### Table 1: Performance characteristics of the sensor. objects. The computed depth map in Figure 8(b) is fairly accurate despite the complex textural properties of the ob- jects. All surface discontinuities and orientation discontinu- ities are well preserved. Figure 9 shows an object apos;s depth map computed as it rotates on a motorized turntable. Such depth map sequences are valuable for automatic CAD model generation from sample objects.

1995

"... In PAGE 6: ...-1994]. The performance evaluation results are summarized in Table1 and discussed in detail in [Na- yar et al.-1994].... ..."

Cited by 62

### Table 1.|SNP Estimation { Maximum Likelihood Surface.

"... In PAGE 10: ... Thus, for a given SNP speci cation, the smaller the R-squared of the regressions, the better the SNP model approximates the true density. In Table1 we present the maximum likelihood surface for three key models: (1) the basic ARCH(1) model, which is SNP(11100); (2) the ARCH model with many lags in the variance (given by SNP(1h100), which has 17 lags in the variance) to approx- imate the GARCH(1,1) speci cation; and (3) the preferred model from our selection procedure, which is SNP(1c121). The preferred model is a general nonlinear process with heterogeneous innovations.... In PAGE 10: ...ith 816 observations for each of three series implying a saturation ratio of 26.3.9 Table 1 indicates that the preferred model performs substantially better than the other two models according to all three model selection criteria. (Insert Table1 here.) The superior performance of the preferred model in matching the data is also re-... ..."