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Table 2. Relationship between gene functions and the two-dimensional arrangement
Table 1: Results for the two-dimensional landscapes.
"... In PAGE 1: ... Each method uses an optimized mutation rate for that method. The results of testing the algorithm on the two-dimensional landscapes are given in Table1 . The Tukey-Kramer test was... ..."
Table 4. Two-dimensional Coordinate Configuration.
"... In PAGE 7: ... The fIrSt is based on point scatter graphs, and the second simulates a terrain representation. Point Visualization The two-dimensional coordinates ( Table4 ) were input to Arc View in the fonD of event files (ESRI terminology) which made them readily available for visualization. The coordinate files were linked to ~e original keyword file (refer back to Table 1) through common identifiers, in straightforward GIS manner.... ..."
Table 3 Results for two-dimensional meshes.
1993
"... In PAGE 8: ... The top level separator for problems \airfoil 1 quot; and \venkat 2 quot; are shown in Figures 1 and 2; the vertices in the separator are marked by the symbol \ . quot; The results for two dimensional problems are summarized in Table3 . For = 1=3, the sizes of the subgraphs are balanced to within a factor of 2.... ..."
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Table 3 Results for two-dimensional meshes.
1993
"... In PAGE 8: ... The top level separator for problems \airfoil 1 quot; and \venkat 2 quot; are shown in Figures 1 and 2; the vertices in the separator are marked by the symbol \ . quot; The results for two dimensional problems are summarized in Table3 . For = 1=3, the sizes of the subgraphs are balanced to within a factor of 2.... ..."
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Table3 Results for two-dimensional meshes.
"... In PAGE 8: ... The top level separator for problems #5Cairfoil 1 quot; and #5Cvenkat 2 quot; are shown in Figures 1 and 2; the vertices in the separator are marked by the symbol #5C#0F. quot; The results for two dimensional problems are summarized in Table3 . For #0B =1=3, the sizes of the subgraphs are balanced to within a factor of 2.... ..."
Table 3. Two-dimensional contingency table
"... In PAGE 9: ... In our study we have two variables, real risk and predicted risk, that can assume only two discrete values, low and high, in a nominal scale. Thus the data can be represented by a two-dimensional contingency table, shown in Table3 , with one row for each level of the variable real risk and one column for each level of the variable predicted risk. The intersections of rows... ..."
Table 3. Two-dimensional contingency table
"... In PAGE 9: ... In our study we have two variables, real risk and predicted risk, that can assume only two discrete values, low and high, in a nominal scale. Thus the data can be represented by a two-dimensional contingency table, shown in Table3 , with one row for each level of the variable real risk and one column for each level of the variable predicted risk. The intersections of rows... ..."
Table 3. Two-dimensional contingency table
"... In PAGE 9: ... In our study we have two variables, real risk and predicted risk, that can assume only two discrete values, low and high, in a nominal scale. Thus the data can be represented by a two-dimensional contingency table, shown in Table3 , with one row for each level of the variable real risk and one column for each level of the variable predicted risk. The intersections of rows... ..."
Table 3. Two-dimensional contingency table
"... In PAGE 9: ... In our study we have two variables, real risk and predicted risk, that can assume only two discrete values, low and high, in a nominal scale. Thus the data can be represented by a two-dimensional contingency table, shown in Table3 , with one row for each level of the variable real risk and one column for each level of the variable predicted risk. The intersections of rows... ..."
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