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Table 3 Time Results First Activity Cycle Group Member Tell Class Give Question Do Analysis Give Feedback Other
in Multi-dimensional Time, Multi-layered Outputs: A Win-win Solution to the Research-teaching Dilemma
TABLE 4: Performance of the SM5.42R/INDO/S2 Model by Solute Functional Class for Solutes Composed of H, C, N, O, F, S, Cl, Br, and I
1999
TABLE 6: Performance of the SM5.42R/INDO/S2 Model by Solvent Functional Class for Solutes Composed of H, C, N, O, F, S, Cl, Br, and I
1999
Table 16. Kernel-based matching outcomes Mean of
"... In PAGE 24: ... In the case of public interest placement, that is indeed the case. Table16 presents the estimated average program effect using kernel matching methods on the identified subset of unconditional participants.31 Note that the control group means are identical to the previous estimate in Table 12b since the composition of the control group does not change.... ..."
Table 1: Examples of translation answer
2001
"... In PAGE 2: ... Each plot type indicates a different numeration as follows: circle: raw number of translation answer candidates; filled circle: number of unique translation answer candidates. Table1 shows examples of translation answer candidates when the retrieval threshold is 0.6.... ..."
Cited by 3
Table 1{Performance bounds for zero propagation delay algorithms Class of Scheduling Range of Property P3 Property P2 Property P1 Algorithms Throughput k N k
1997
"... In PAGE 13: ...3 For gt; 12, S 6, and n 3, no scheduling algorithm in the class CONTIN- UOUS STATIC has any property P1{P4. Table1 summarizes the throughput and delay characteristics of the scheduling algorithms pre- sented in this and the previous section. The last three columns list the upper bounds for k N k,... ..."
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Table 1. Classification Results for a Sample news Frame.
"... In PAGE 6: ...lasses. A confidence value of 1.0 indicates complete confidence in a class, and a value of 0.0 indicates complete lack of confidence. Table1 shows an example output for a news frame. To calculate the recognition rate, we chose the class with the maximum confidence value for each frame, and then compute the overall correct classification rate by comparison with the ground truth obtained from visual classification of the frames.... ..."
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Table 2 Vertical movement behaviours of the artificial individuals dur- ing nighttime and daytime, respectively, ranked by frequency across ten simulationsa
"... In PAGE 7: ... Section 3.3), we ranked the behaviours by fre- quency of occurrence in each run, and used the median of the rank distributions to classify the results of the ten runs ( Table2 ). Only 19 of the 49 a fish can vary between 0 and 4000 units.... In PAGE 8: ...332 classes of possible patterns were represented in the ten final artificial populations. The five most fre- quent classes are highlighted in Table2 , and the typical vertical movements in these five classes are shown in Fig. 4.... In PAGE 8: ... The classifi- cation criteria are the same used for the artificial fishes (cf. Table2 ), and are based on data from the references shown. Table 2 Vertical movement behaviours of the artificial individuals dur- ing nighttime and daytime, respectively, ranked by frequency across ten simulationsa... ..."
Table 2. Correlations of neighbour-exchanges with gaps
"... In PAGE 8: ...contains the scatter-plots for both intervals, and Table2 (p. 301) lists the correlation coefficients.... In PAGE 9: ...o similar sorts of gaps. Fig. 4 shows scatter-plots of neighbours exchanged by cells experiencing both classes of gaps for both intervals. The correlations, shown in Table2 , are not significant. In the course of gathering gap data, we noticed that there seemed to be almost no individual occurrences of the phenomenon we were looking for.... ..."
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