### Table 3. Three-dimensional K-optimal lattice rules

"... In PAGE 7: ... One sets NL = NU = Nopt. The list of rules in Table3 was obtained as follows. For each value of ,thesearch module was used with NU large and NL =max(NME(3; );NCL(3; )) as given in (1.... In PAGE 7: ... Finally, the list of matrices was processed to remove all symmetric equivalents. Note that, without the second run, one of the entries for each of = 5 and 11 in Table3 would have been missed. The 4-octahedron has eight facet-pairs.... In PAGE 12: ....2. Three-dimensional lattice rules. For every abscissa count we have listed, we have speci ed at least one cubature rule. Table3 contains speci cations of thirty- one K-optimal rules. This list is complete in the sense that every K-optimal rule of enhanced degree thirty or less is included here or is symmetrically equivalent to one listed here.... ..."

Cited by 2

### Table 1: An example of a three-dimensional table.

1993

"... In PAGE 3: ...Table1 has three categories, D1, D2 and D3; thus, it is a three-dimensional table. The logical relationship among the data items of a table is the association between labels and entries.... In PAGE 3: ... Each entry is associated with one or more sets of labels of di erent categories simultaneously. For example, in Table1 , entry e1 is associated with a set of labels fd11; d21; d311g simultaneously; entry e7 is associated with both fd12; d21; d312g and fd12; d22; d312g simultaneously. The data items and the logical relationship among them provide the logical structure of the table, which is the primary information that a table conveys and which is independent of its format.... In PAGE 6: ... This function guarantees that every entry in E is mapped from at least one ff1; ; fng 2 D1 n. Using this model, Table1 can be abstracted by (3; fD1; D2; D3g; E; ), where D1 = fd11; d12g D2 = fd21; d22; d23g D3 = fd31; d32g d31 = fd311; d312g d11 = d12 = d21 = d22 = d23 = d32 = d311 = d312 = fg E = fe1; e2; e3; e4; e5; e6; e7; e8; e9g (fD1:d11; D2:d21; D3:d31:d311g) = e1; (fD1:d11; D2:d21; D3:d31:d312g) = e2; (fD1:d11; D2:d22; D3:d31:d311g) = e3; (fD1:d11; D2:d22; D3:d31:d312g) = e3; (fD1:d11; D2:d23; D3:d31:d311g) = e4; (fD1:d11; D2:d21; D3:d32g) = e5; (fD1:d11; D2:d22; D3:d32g) = e5; (fD1:d11; D2:d23; D3:d32g) = e5; (fD1:d12; D2:d21; D3:d31:d311g) = e6; (fD1:d12; D2:d21; D3:d31:d312g) = e7; (fD1:d12; D2:d22; D3:d31:d312g) = e7; (fD1:d12; D2:d23; D3:d31:d312g) = e8; (fD1:d12; D2:d21; D3:d32g) = e9; (fD1:d12; D2:d22; D3:d32g) = e9; (fD1:d12; D2:d23; D3:d32g) = e9; 4.2 Basic operators in the tabular model We rst describe the syntax of all basic operators in function form by giving the operator identi ers and the types of their operands and results.... ..."

Cited by 2

### Table 6: Head-Driven Three-Dimensional Extensions: Ac- curacy results for parsing the devest (section 0)

"... In PAGE 9: ... We set our baseline at the (0, 0, 0) coordi- nate and evaluate models that combine one, two and three dimensions of parametrization. Table6 shows the accuracy results for parsing section 0 using the resulting models. The first outcome of these experiments is that our new baseline improves on the accuracy results of a simple treebank PCFG.... ..."

### Table 3. Guidelines for positioning atmosphere content in the three-dimensional model space of warmth, activity, and attention Factor Lights Audio Video

"... In PAGE 9: ... A video artist was involved in creating video material for the atmosphere model. The guidelines listed in Table3 were used to select and design the media content for the model, but they should only be considered as rules of thumb, since they are based on the results of the rating sessions for the mood boards. The resulting model space was validated by users.... ..."

### Table 2 Three-dimensional structures of ribosomal proteins

1998

"... In PAGE 14: ... Someday, useful information may be gained by building these structures into low-resolution ribosome mod- els. Table2 lists the structures available, and Figures 6 and 7 display their topologies. Several conclusions have already emerged.... ..."

Cited by 2

### Table 4 The 45 combinations of base pairing patterns found in the set of loop 785-797 three-dimensional structures gen- erated by the MC-SYM program.

"... In PAGE 7: ... The conformational search space size of the selected spanning tree is 1023 corresponding to 3375 different combinations of base pairing patterns. MC-SYM generated 33998 consistent three- dimensional structures, composed of 45 different combinations of base pairing patterns (see Table4 ). The RMS deviation among the 45 classes vary from 2.... ..."

### Table 1: Three-dimensional input data in which each sample vector x consists of the RGB (red-green-blue) values of the color shown in the rightmost column.

1997

"... In PAGE 15: ...ransformation (Kohonen et al., 1984; Kohonen, 1988). 2.1 The Self-Organizing Map algorithm Assume that some sample data sets (such as in Table1 4) have to be mapped onto the array depicted in Figure 1; the set of input samples is described by a real vector x(t) 2 Rn where t is the index of the sample, or the discrete-time coordinate. Each node i in the map contains a model vector mi(t) 2 Rn, which has the same number of elements as the input vector x(t).... In PAGE 17: ... Each map node, visualized as a circle on the grid, serves as a model, mi, or to use another term, a prototype of a class of similar inputs. The line diagrams inside the circles denote the three RGB values of Table1 . For instance, the nodes on the lower left corner correspond to colors which have high values of all the components, i.... In PAGE 18: ... Each circle corresponds to a map node. Inside the circle the model vector consisting of the three RGB values from Table1 is visualized. The initial value of the learning step size, alpha0, was 0:2 and the neighborhood width was initially 5.... In PAGE 20: ...green-yellow pale green pale- goldenrod antique-white papaya-whip linen old lacebeige floral white khaki light- goldenrod moccasinwheat mint creamalice blue ghost whitewhite dark- sea green dark khaki burlywoodtan light pinkpink thistle lavender dark salmon rosy brown plum light blue pale turquoisepowder blue dark orange goldenrod coral sandy brown light coral hot pink orchid violet sky blue salmon pale- violet red medium-orchid medium-purple chocolatedark- goldenrod indian red medium- violet red violet red dark orchiddark violet purple blue violet maroon slate blue olive drab sienna brown firebrick slate gray steel blue cornflower- blue royal blue dark olive-green dark slate-blue cadet blue medium sea-green forest greenlime green dark green black midnight-blue navy blue light sea-green medium- turquoise turquoisedark- turquoise Figure 3: A map of colors based on their RGB values. The color symbols in the rightmost column of Table1 as used in labeling the map. The best matching unit is searched for each input sample and that node is labeled accordingly.... In PAGE 25: ... When all di erent word forms in the input material are listed, a code vector can be de ned to have as many components as there are word forms in the list. As an example related to Table1 shown earlier, the color symbols of Table 2 are here replaced by binary numbers that encode them. One vector element (column in the table) corresponds to one unique color symbol.... ..."

Cited by 25

### Table 2 Figure 2: Block representation of a three dimensional binary variable

"... In PAGE 12: ...Table2 shows the parameter estimates together with their standard errors using a classical log-linear model. No classical independency is acceptable because of the highly signi cant tree-term inter- action.... ..."

### Table 2 Figure 2: Block representation of a three dimensional binary variable

1996

"... In PAGE 8: ... 1 0 = 1 1 = 0:147236(0:04991) 2 0 = 2 1 = 0:54974(0:04991) 3 0 = 3 1 = 0:44951(0:04991) 2-factor 1;2 0;0 = 1;2 0;1 = 1;2 1;0 = 1;2 1;1 = 0:09687(0:04991) 1;3 0;0 = 1;3 0;1 = 1;3 1;0 = 1;3 1;1 = 0:20522(0:04991) 2;3 0;0 = 2;3 0;1 = 2;3 1;0 = 2;3 1;1 = 0:14129(0:04991) 3-factor 1;2;3 0;0;0 = = 1;2;3 1;1;1 = 0:11875(0:04991) Table 2 Table2 shows the parameter estimates together with their standard errors using a classical log-linear model. No classical independency is acceptable because of the highly signi cant tree-term inter- action.... ..."

Cited by 2

### Table 6. Peak heap use (in K bytes) for Haskell versions with three-dimensional intermediate forms

1997

"... In PAGE 15: ... All the programs were compiled with -O optimization. Table6 shows the peak heap consumption of the Haskell codes that use three- dimensional intermediate arrays, and table 7 shows the same information for the matrix-of-vectors codes. These tables also compare the Glasgow and Chalmers com- pilers.... ..."

Cited by 6