### Table 3: A trace of Algorithm 4: generation of the rst six global concepts for the example in Figure 3. As an illustration of the way Algorithm 4 works, we provide the trace of its execution on the rst six product nodes that generate global concepts. The related values of the R function for each of the nodes as well as for each of their lower covers in L are given in Table 3. The table also provides the global concepts which are actual lower covers of the generated concept together with the respective values of R which helped generate them.

2002

Cited by 6

### Table C.2: Registration results C.1 Local dissimilarities of the surfaces The algorithm assumes that the surfaces are related through a global a ne transfor- mation. Therefore, when given the task of registering two surfaces, the algorithm only captures the global transformation and does not take into account the local features of the surfaces. Moreover, it does not deform a surface to match the other surface. One con- sequence of this behavior is that the algorithm can not precisely register the CT and the Cyberware datasets coming from two di erent individuals, since the facial skin surfaces of di erent individuals are not related through a global transformation. The following example illustrates this shortcoming of the algorithm. S1 and S2 are transformed using the transformation parameters listed in Table C.1. The transformed surfaces are called S3 and S4 respectively. We now register S1 with S3 and S4 and compute the ISD values.

### Table 1: Speedup gains relatively to second best algorithm

"... In PAGE 7: ... It is clear that the new algorithm outperforms the other al- gorithms in all cases. Speedup gain for each scene relatively to the second best algorithm is shown in Table1 . This is due to a huge reduction on irradiance cache misses, compared with the other parallel approaches, as illustrated in Figure 8 for the Kalabsha temple and 24 processors.... ..."

### Table 1: Illustration of retrieval algorithms

1998

"... In PAGE 2: ... We refer to this method as the word-based query processing. Table1 shows nine methods which have been implemented in our systems.... ..."

Cited by 4

### Table 1 illustrates our algorithm in pseudo-code. The algorithm requires three inputs: a dictionary of lexical analogies A in which the lexical analogues of many word-pairs are listed, a set L = {L1, ..., Lk} of lexical semantic relations of inter- est, and a set ELi for each Li that contains a small number of sample instances of the relation Li. An example of the input is L={part-of } and EL1={(finger, hand),(beak, bird)}.

"... In PAGE 2: ... Table1 . Algorithm for Learning Lexical Semantic Relations The result of our algorithm is that each ELi is rapidly expanded from a small set of samples to a large set of instances by iteratively incorporating the lexical analogues of the samples.... ..."

### Table 8: Illustration of retrieval algorithms

"... In PAGE 11: ... We refer to this method as the word-based query processing. Table8 shows nine methods whichhave been implemented in our systems. We use M 5 and M 6 whichareword-based in our Chinese TREC experiments.... ..."

### Table 1: Illustration of retrieval algorithms

"... In PAGE 2: ... We refer to this method as the word-based query processing. Table1 shows nine methods whichhave been implemented in our systems.... ..."

### Table 8: Illustration of retrieval algorithms

1997

"... In PAGE 11: ... We refer to this method as the word-based query processing. Table8 shows nine methods which have been implemented in our systems. We use M5 and M6 which are word-based in our Chinese TREC experiments.... ..."

### Table 1: Literature containing algorithms answering questions in invariant theory and their implementations. for this class of algorithms). New contributions are the use of the multigraded Hilbert series driven Buchberger algorithm [9, 22] for computation of relations, completeness of equivariants (B. 2.)), restriction of completeness to certain degree (A.2b.), B. 2b.)), mem- bership of free module. Restriction with respect to various gradings are the key to the partial completeness questions. This is illustrated by examples which have been computed on a Dec Alpha workstation. These new ideas mainly improve the e ciency of existing algorithms. The algorithmic treatment for continuous groups has been implemented and tested for the rst time.

"... In PAGE 4: ... However this is not well recognized by the dynamical systems community. Table1 summarizises the relevant books and articles so far they contain e cient algorithms and gives an overview of implementations. Invar [29] and Symmetry [19] are implemented in Maple while an implementation for C.... ..."

### Table 3 provides some numerical assessment of our method. During this experi- ment, a cut cavity (in the shape of an implant) is first preplanned relative to the femur. Then the cut cavity is perturbed with various transformations, and a simulated cutting of the perturbed cavity is executed on the femur. Then the Iterative Cavity Location algorithm is employed to recover the perturbation transformation. Figure 6 illustrates the images simulated in trial 4 of table 3.

1999

"... In PAGE 9: ... Table3 Results of Recursive Cavity Location Algorithm 7. Discussions and Future PlansThe system and method described in this paper demonstrates the feasibility of cutting a precise pocket using the C-arm fluoroscopy.... ..."

Cited by 1