### Table 1: Number of triples for the most common interactions of the HIV-1 database, after removing the distinction in directionality and the triples with more than one interaction.

2005

"... In PAGE 3: ...); we collapsed these pairs of related interactions into one5. Table1 shows the list of the 25 interactions of the HIV-1 database for which there are more than 10 triples. For these interactions and for a random subset of the protein pairs a1a2a1 (around 45% of the total pairs in the database), we downloaded the corresponding full-text papers.... ..."

Cited by 1

### TABLE 2: Distinctions and Complementary Nature of Tutoring and Self-Directed Learning

2005

Cited by 1

### Table 1: Average penetration depth for mesh vs. direct parametric tracing of di erent models. Sample points is the number of distinct contact evaluations.

1997

"... In PAGE 7: ... Sample points is the number of distinct contact evaluations. Table1 shows that the average penetration depth for the parametric method was 1/3 to 1/2 the penetration depth of the point mesh method. There is a non-intuitive relation- ship in the results between penetration depth and model complexity, with smaller penetration depths produced by the more complex models.... ..."

Cited by 53

### Table 1: Average penetration depth for mesh vs. direct parametric tracing of di erent models. Sample points is the number of distinct contact evaluations.

1997

"... In PAGE 7: ... Sample points is the number of distinct contact evaluations. Table1 shows that the average penetration depth for the parametric method was 1/3 to 1/2 the penetration depth of the point mesh method. There is a non-intuitive relation- ship in the results between penetration depth and model complexity, with smaller penetration depths produced by the more complex models.... ..."

Cited by 53

### Table 3: Time for Reading Distinct Sections

1995

"... In PAGE 17: ...Figure 11: The Distinct Sections listed in Table3 (not to scale)... In PAGE 18: ... Finally,in row VIII, the sections haveoverlap in both dimensions and the Extended Two-Phase Method again performs better. Table3 compares the performance of the Extended Two-Phase Method and the Direct Method for reading distinct sections. Figure 11 shows approximately where these sections are located in the array.... In PAGE 19: ... Table 4 compares the performance of the Extended Two-Phase Method and the Direct Method for writing distinct sections. The sections chosen are the same as those for reading in Table3 , and are shown in Figure 11. We use the most general algorithm for writing in the Extended Two-Phase Method, which requires an extra read for each write.... ..."

Cited by 1

### Table 4: Time for Writing Distinct Sections

1995

"... In PAGE 19: ...1 Performance We only consider the case where each processor writes a distinct section to the le, because it is unlikely that processors will want to write overlapping or common sections. Table4 compares the performance of the Extended Two-Phase Method and the Direct Method for writing distinct sections. The sections chosen are the same as those for reading in Table 3, and are shown in Figure 11.... ..."

Cited by 1

### Table 1: 13 Temporal Interval Relations The temporal interval algebra essentially consists of the topological relations in one dimensional space enhanced by the distinction of the order of the space. The order is used to capture the directional aspects in addition to the topological relations. We consider 12 directional relations in our model and classify them into following three categories: strict directional relations: north, south, west, and east; mixed directional relations: northeast, southeast, northwest, and southwest; 12

1996

"... In PAGE 13: ...Table1 ) for representing and reasoning about temporal relations between events represented as intervals. These temporal relations have been cited by others [Bee89, SF95, NSN95] for their simplicity and ease of implementation with constraint propagation algorithms.... ..."

Cited by 23

### Table 3: Space requirements for di erent representa- tions and times spent to nd all possible diagnoses for a given ECG description, averaged over all 3096 distinct ECGs.Notice the very high directionality bias of the one- level heart model in Table 3. When the model is used in the `forward apos; direction, the average time to derive an ECG for a given Arr is only 0.063 seconds (this is con- sistent with the 50.35 seconds for the generate-and-test, where the model is applied 943 times in the `forward apos; direction, once for each distinct Arr). In contrast, the average `backwards apos; application (for diagnosis) requires as much as 66.30 seconds. As a consequence, even the 14

1991

"... In PAGE 14: ... Diagnostic e ciency is the time needed to nd all possible diagnoses for a given ECG, and was measured on all 3096 distinct ECG descriptions at the detailed level. Results in Table3 are the average times... ..."

Cited by 27

### Table 1: Correlation between perspective and direction method

in Conveying Routes: Multimodal Generation and Spatial Intelligence In Embodied Conversational Agents

"... In PAGE 16: ... Recalling the distinction between route and survey perspectives [Emmorey, Tversky, and Taylor, 2000], there was a strong correlation between the direction method and the perspective taken. As Table1 indicates, speech and gesture (SG) directions coincided with the route ... ..."

### Table 1. Distributions of k0 and k1 Conditional on the number of components (k0 and k1) for each Gibbs iteration, the distinct normal means and all other parameters were obtained. This allows for direct inference on the characteristics of each component of the mixture distribution (West and Cao (1993); Escobar and West (1995)). The approximate predictive noise density appears in Figure 2(a), illustrating the match with the observed noise sample 10

"... In PAGE 10: ... All deconvolution analyses were conditional on k0 and k1. For these priors and this data set, the induced prior probabilities are summarized in the columns labeled \Prior quot; in Table1 , for later comparison with the posteriors.... In PAGE 11: ...532, and so forth. The height of the third line in Figure 2(c) is very close to zero, corre- sponding to the posterior probabilities for k0 in the second column of Table1 . We note that, though the prior for the noise distribution was heavily in favor of a single normal distribution, the posterior probabilities strongly suggest two components; the map from prior to posterior for k0 dramatically indicates the data support for two components.... In PAGE 11: ... We note that, though the prior for the noise distribution was heavily in favor of a single normal distribution, the posterior probabilities strongly suggest two components; the map from prior to posterior for k0 dramatically indicates the data support for two components. For the signal distribution, a more typical picture emerges in comparison of columns three and four of Table1 . Though the prior for k1 is heavily concentrated at a single signal level, the posterior is dramatically di erent, supporting at least ve components, and most likely 5, 6 or 7.... ..."