### Table 1: Low-degree frequency datasets

"... In PAGE 1: ...l., 1994b). 2. DATA The inverted data are combinations of the frequencies of the low-degree modes, taken from each of the low-degree datasets ( Table1 ), and 598 frequencies of intermediate- degree modes (l = 4?140, = 1:5?3:0mHz), observed at BBSO in 1988 (Libbrecht et al. 1990).... ..."

### Table 2: Inet 2.0 Topology Generator: The table summarizes the performance of the data reduction on various networks generated with the generator in [8]. We constructed networks of 5000, 7500, and 10000 vertices using the default configuration and varying over the parameter d (expressing the fraction of low-degree vertices, see [8] for details) in order to obtain networks with various numbers of edges. The columns show the performance of our data reduction, reporting on the time needed (in seconds), the amount by which the networks were reduced, and the size of an optimal dominating set (DS) as computed by our method.

2003

Cited by 13

### Table 2: Inet 2.0 Topology Generator: The table summarizes the performance of the data reduction on various networks generated with the generator in [8]. We constructed networks of 5000, 7500, and 10000 vertices using the default configuration and varying over the parameter d (expressing the fraction of low-degree vertices, see [8] for details) in order to obtain networks with various numbers of edges. The columns show the performance of our data reduction, reporting on the time needed (in seconds), the amount by which the networks were reduced, and the size of an optimal dominating set (DS) as computed by our method.

### Table 3: Inet 2.0 Topology Generator: The table summarizes the performance of the data reduc- tion on various networks generated with the Inet topology generator [Jin et al., 2001]. We constructed networks of 5000, 7500, and 10000 vertices using the default configuration and varying over the pa- rameter d (expressing the fraction of low-degree vertices, see [Jin et al., 2001] for details) in order to obtain networks with various numbers of edges. The columns show the performance of our data reduction, reporting on the time needed, the amount by which the networks were reduced, and the size of an optimal dominating set (DS) as computed by our method.

2003

"... In PAGE 10: ...uced by the Internet topology generators Inet [Jin et al., 2001] and BRITE [Medina et al., 2001]. We refer to the given papers for any details concerning the data generation process. Table3 gives our results and the parameter settings we used for generating the corresponding networks from Inet 2.... ..."

Cited by 13

### Table 2 gives the ratios of these hop counts and hop counts of SP algorithm (i.e. flooding rates). These ratios are close to optimal (1) for higher degree graphs, and reasonable for low degree graphs. The largest ratio found was 4.71 for n=100, d=4. Table 3 gives the EHCs for DFS based QoS routing. Table 4 presents ratios of EHCs and hop counts by SP algorithm. The largest ratio found is 1.34, meaning that DFS does provide almost shortest path routes for QoS routing in localized manner. This excellent ratio is obtained for the critical case of low degree graphs, while higher degree graphs gave almost perfect routes, with ratios very close to 1.

2000

"... In PAGE 10: ...31 1.28 Table2 . Ratios of average hop counts of DFS and SP algorithms Table 2 gives the ratios of these hop counts and hop counts of SP algorithm (i.... ..."

Cited by 33

### Table 2 gives the ratios of these hop counts and hop counts of SP algorithm (i.e. flooding rates). These ratios are close to optimal (1) for higher degree graphs, and reasonable for low degree graphs. The largest ratio found was 4.71 for n=100, d=4. Table 3 gives the EHCs for DFS based QoS routing. Table 4 presents ratios of EHCs and hop counts by SP algorithm. The largest ratio found is 1.34, meaning that DFS does provide almost shortest path routes for QoS routing in localized manner. This excellent ratio is obtained for the critical case of low degree graphs, while higher degree graphs gave almost perfect routes, with ratios very close to 1.

"... In PAGE 12: ...31 1.28 Table2 . Ratios of average hop counts of DFS and SP algorithms Table 2 gives the ratios of these hop counts and hop counts of SP algorithm (i.... ..."

### Table 1: Table of Relative Similarity Scores for Example Frag- ments. H { High degree of overlap; M { Medium degree; L { Low degree.

1997

"... In PAGE 6: ...everse orientation. This orientation is lost during the fragmentation process. The assembly process then compares the individual base pair sequences for the fragments and, using this information, assembles a consensus sequence for the parent DNA. Table1 shows what the overlap comparison for the fragments in the gure would show. For example, fragment f2 is wholly contained within the stretch of the parent DNA occupied by fragment f9.... In PAGE 6: ... Since f2 is also a large fragment, this overlap is designated H for high-degree of overlap in the table. The other entries Table1 can be determined from Figure 1 using the same approach. Any empty locations in the table represent essentially random similarities, and hence are not necessarily zero.... In PAGE 15: ... Hence, we had concerns about potential interactions among the operator rates. Combining these concerns with our computing resource constraints (a Sparc workstation), we opted for a replicated 24 full factorial design with rates speci ed in Table1 . We had the ability to observe results of the full factorial design as they were produced so the run-order was set to be a half-fraction, the other half-fraction and then the replicates of the design.... ..."

Cited by 8

### Table 3 shows the match between the interference and faults. So, if we use the interference detection algorithm to predict faults, the hit rate in high degree parallel change set is much higher than that in the low degree set.

"... In PAGE 6: ...0%) Control 17 2 0 2 (100.0%) Table3 The match between semantic interference fragments and faulty code fragments in the three sets of changes. In the three sampled sets, the higher the parallelism is, the lower the false positive is.... ..."

### Table 1: A comparison of the various kinetic data structure based methods: f is the number of facets in the final triangulation, em the number of flips (events) caused by motion m, S(d) is the cost to solve a polynomial of degree d. The cost column is how many certificate functions will be generated and solved by the kinetic Delaunay update. The determinant cost is an estimate the in initialization cost in units of a the cost of a static determinant evaluation. Note that the base costs of the low degree kinetic data structures are very close to that of rebuilding. This agrees with our experimental findings. The cost for quadratic trajectories is too high to be of practical interest.

### Table 8.1. CycDeco: CPU-time in sec for the calculation of the relevant cycles and the relevant, shortest, unique shortest and essential cycles as well as the interchangeability classes of a biconnected random graphs with low degrees ( rst and second part) and high degrees (third part) (x = deg jV j 1). (average values over 100 (jV j lt; 100) and 10 (jV j 100) graphs) (using a Pentium III (Coppermine), 733 MHz, 1024 RAM) average number of nodes

2001