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Table 2. Twelve types of design features
"... In PAGE 3: ... The largest size is set as 8cm*8cm to fit in a PowerPoint slide. Twelve types of design features as shown in Table2 have been identified for the investigation. Table 2.... ..."
Table 1: Twelve primitive agent types
"... In PAGE 10: ... A complete agent type is a maximal consistent set of constraints. There are twelve primitive agent types, which are listed in Table1 together with the cor-... ..."
Table 1: Pronunciation models for the twelve months of the
1996
"... In PAGE 3: ....1. Segment-based system using trajec- tory models In this experiment, phoneme is used as the basic unit in recognition. Table1 depicts the pronunciation models for... ..."
Cited by 11
TABLE 3. Twelve pairs of reciprocal interciters in Globenet.
2004
Cited by 11
Table 2. Twelve combination of edges of pentagon.
2005
"... In PAGE 13: ..., there are a total of 12 unique combinations (see Table 2) (SUGIMOTO, 1999; SUGIMOTO and OGAWA, 2000, 2003a, 2003c, 2005). For example, the combination [11111] in Table2 is the pentagon with all the identical edge-lengths; i.e.... In PAGE 15: ...3). Next, for tiles, we find that the pentagons can be classified into 12 kinds by the number of equal-length edges and their positions (see Table2 ) (SUGIMOTO, 1999; SUGIMOTO and OGAWA, 2000, 2003a, 2003c, 2005). Then, we see that the tiling by congruent convex pentagon is impossible when all edges of convex pentagon are of different length (see Theorem 4) (SUGIMOTO and OGAWA, 2003c).... In PAGE 15: ... On the other hand, it is known that the equilateral convex pentagons which can tile the plane have to belong to type 1, 2, or 7 in the present list. Among 12 cases of pentagons of Table2 , the two cases were solved. But, the investigations about other 10 cases have not been completely finished yet.... ..."
Table 2.1: Twelve CG methods.
Table 1. Concise description of the twelve implemented agents
"... In PAGE 3: ... In choosing the paradigms we strived to maintain a balance between high level, logic based approaches and low level, physics oriented models; be- tween imperative programming, declarative approaches and learning from ba- sics as well as between anthropomorphic or biologically inspired models on one hand and pragmatic, performance oriented approaches on the other. The imple- mented agents are concisely described in Table1 . The developers were instructed to develop paradigm-pure implementations and to design the agents such that... ..."
TABLE V The results of learning on the twelve fuzzified neural
Table 2: Results of the twelve entity layout problem.
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