### Table 1: Permutations and negations for multi view arrange- ments

### Table 1: Permutations and negations for multi view arrange- ments

### Table 4: Recognition statistics without ambiguity ltering. The arrange- ment of this table is the same as that in Table 3.

"... In PAGE 12: ... First, it is evident from both tables that using more measurement func- tions usually increases recognition accuracy and reduces image ambiguity. In addition, the dramatic increase in recognition accuracy in Table 3 versus Table4 re ects the ubiquity of ambiguous images in the environment. The... ..."

### Table V. Computation time (msec) for DPRTT with lazy iterative arrange- ment vs. DPR algorithms, for Grids

### Table 1. Identification of known membrane protein helix packing arrangements in the computer-generated fold librariesa

1999

"... In PAGE 4: ... If real helix-packing arrangements are drawn from the same pool as the computer-generated arrange- ments, roughly 80% of the helix-packing arrangements found in known membrane protein structures are expected in the 13 library, and almost all of them should be in the 103 library. The number of the helix-packing arrangements, extracted from known membrane protein structures, that are found in the computer- generated structure libraries is shown in Table1 . Of the 87 helix- packing arrangements extracted for three to seven helices, 64 ~74%! were found in the 13 libraries and 80 ~92%! were found in the 103 libraries.... ..."

### Table 1: Percent time working in each coupling style and physical arrangement. Arrangement categories are in increasing order of average distance between participants. Coupling styles range from working closely together (left) to working independently (right).

2006

"... In PAGE 8: ... As we expected, when collaborators worked more closely together, they stood physically closer, and when they worked independently, they stood further apart. This can be seen as a dark diagonal trend from the top left to bottom right of Table1 . Although this effect is complicated by the fact that participants were physically closer when working on the same sub-problem, it corresponds with results from our first study, which did not have spatially separated sub- problems.... ..."

Cited by 4

### Table 1. Arrangements of n 6 planes: Sequence of codimensions of components of Vn?2|where ik stands for i repeated k times|and number of 2- and 3-torsion points on V1. of n 6 planes is homotopy equivalent to the complement of one of the arrange- ments in this shorter list. Table 1 shows that there are no repetitions among the homotopy types of these 20 arrangements. Hence, we have the following. Theorem 9.4. For 2-arrangements of n 6 planes in R4, the homotopy types of complements are in one-to-one correspondence with the rigid isotopy types modulo mirror images.

2000

### Table 1: A best arrangement of N streams and the associated minimal e ective bandwidth. Given that N ongoing streams are scheduled according to u , a new stream can be added to the existing ones resulting in a best arrangement of (N +1) streams without disrupting the original structure of the N streams. In other words, u of (N + 1) streams can be obtained by simply concatenating a single number to u of N streams. When N streams are arranged according to u and N L, the removal of any stream will still result in a best arrangement of N ? 1 streams. When N gt; L, only the removal of certain streams preserves the optimality of the arrangement. As N increases, Cmin(N) decreases slowly in a non-monotonic manner. The asymptotic value of Cmin(N) can be obtained by taking the limit of Cmin(N) in (15) with respect to N. For large N, w N=L and m N=Q. Thus, C min 4 = lim N!1 Cmin(N) = (1=L)Imax + (1=Q ? 1=L)Pmax + (1 ? 1=Q)Bmax

1997

"... In PAGE 12: ...Table1 provides the form of u and the expression for Cmin(N). Although the structure of u is quite intuitive, proving its optimality is not trivial.... In PAGE 14: ... An inspection of (14) reveals that when N streams are arranged according to u , there are exactly m+1 streams whose phases di er, pairwise, by a nonnegative multiple of Q. Among those, w + 1 streams belong to the same phase (m and w were de ned in Table1 ). It is obvious that C(u ; N) is obtained from a phase i in which ri = w +1 and zi = m + 1 ? (w + 1) = m ? w.... ..."

Cited by 16

### Table 1: A best arrangement of N streams and the associated minimal e ective bandwidth. Given that N ongoing streams are scheduled according to u , a new stream can be added to the existing ones resulting in a best arrangement of (N +1) streams without disrupting the original structure of the N streams. In other words, u of (N + 1) streams can be obtained by simply concatenating a single number to u of N streams. When N streams are arranged according to u and N L, the removal of any stream will still result in a best arrangement of N ? 1 streams. When N gt; L, only the removal of certain streams preserves the optimality of the arrangement. As N increases, Cmin(N) decreases slowly in a non-monotonic manner. The asymptotic value of Cmin(N) can be obtained by taking the limit of Cmin(N) in (15) with respect to N. For large N, w N=L and m N=Q. Thus, C min 4 = lim N!1 Cmin(N) = (1=L)Imax + (1=Q ? 1=L)Pmax + (1 ? 1=Q)Bmax

1997

"... In PAGE 12: ...Table1 provides the form of u and the expression for Cmin(N). Although the structure of u is quite intuitive, proving its optimality is not trivial.... In PAGE 14: ... An inspection of (14) reveals that when N streams are arranged according to u , there are exactly m+1 streams whose phases di er, pairwise, by a nonnegative multiple of Q. Among those, w + 1 streams belong to the same phase (m and w were de ned in Table1 ). It is obvious that C(u ; N) is obtained from a phase i in which ri = w +1 and zi = m + 1 ? (w + 1) = m ? w.... ..."

Cited by 16