### Table 12: Multi-dimensional categorization

2006

"... In PAGE 11: ...Multi-Conference Information Systems (MKWI06), Passau, Germany, 2006. Table12 exemplarily illustrates the multi-dimensional categorization of metrics. Table 12: Multi-dimensional categorization ... ..."

Cited by 2

### Table 5: Performance of table look up intrusion detection algorithm for clear and stealthy attacks.

1999

"... In PAGE 6: ...Table 5: Performance of table look up intrusion detection algorithm for clear and stealthy attacks. Table5 shows the performance of the algorithm in detecting clear versus stealthy attacks. Stealthy attacks attempt to hide perpetrator apos;s actions from someone monitoring the system or from an intrusion detection system.... ..."

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### Table 7.5: Multi-dimensional vote and quorum assignment for the 3x2 grid system

### Table 1: Multi-dimensional Characterization of a Social Actor (Lamb amp; Kling, forthcoming)

2002

"... In PAGE 16: ... Acknowledgements This research has been funded by National Science Foundation, Information and Intelligent Systems, Computation and Social Systems Awards #98-76879 and #00- 96169. 5 A more detailed analysis of the social actor characteristics for Affiliations, Environments and Identities (see Table1 ) has not been attempted in this paper, but is part of my ongoing intranet ... ..."

### Table 5: Performance of table look up intrusion detection algorithm for clear and

"... In PAGE 6: ...Table 5: Performance of table look up intrusion detection algorithm for clear and stealthy attacks. Table5 shows the performance of the algorithm in detecting clear versus stealthy attacks. Stealthy attacks attempt to hide perpetrator apos;s actions from someone monitoring the system or from an intrusion detection system.... ..."

### Table 4: Multi-Dimensional Resource Models

"... In PAGE 7: ... This will typically be a negative term (= profit per accepted customer). Non-Existent - Existent C Table 5: Cost Model Elements Table4 : Multi-Dimensional Resource Models... ..."

### Table 3: Multi-dimensional DISC algorithm

"... In PAGE 8: ... Given two locations represented by longitudes and latitudes, they are near to each other only if their longitudes and latitudes are close to each other. To cluster objects of multiple attributes, DISC can be extended to M-DISC ( Table3 ). The generated multi-dimensional TAHs are called MTAHs.... ..."

### Table 5. Multi-Dimensional Parametriza- tion of Treebank Grammars (Head-Driven Models are Marked h 6 = 1): F 40; FALL Accuracy Results on Section 0.

"... In PAGE 6: ... We set our baseline model at the (0; 0; 0) point of the coordinate-system and com- pared its performance to a simple treebank PCFG and to di erent combinations of parameters. Table5 shows the accuracy results for parsing section 0 for all models. The rst outcome of our experiments is that our head-driven baseline performs slightly better than a vanilla treebank PCFG.... ..."

### Table 1, i.e. k = PBc + Bp + b and l = Bc + b. The distribution basis for a multi-dimensional array can be expressed as a tensor product of the distribution bases for each dimension.

1994

"... In PAGE 5: ...Table1 : Index mapping functions for regular data distributions. BLOCK CYCLIC CYCLIC(b) local to global k = p(dN=Pe) + l k = lP + p k = (l div b)bP + bp + l mod b global to local l = k mod dN=Pe l = k div P l = (k div Pb)b + k mod b global to proc p = k div dN=Pe p = k mod P p = (k div b) mod P k global index 0 k N ? 1; l local index 0 l lt; db ?dN=(Pb)e ; p processor 0 p lt; P.... In PAGE 5: ... Techniques developed in [11] can be used for the array redistribution in the general case. For identity alignments, the relationships between the global index, the local index and the processor index for regular data distributions of a one-dimensional array are shown in Table1 . The indexing for arrays A and A loc begins at zero and the processors are numbered from 0 to P ? 1.... In PAGE 8: ... For example, under a BLOCK distribution the array is partitioned into segments of size NP . The relationship between the global index k, the processor index p, and the local index l as shown in Table1 can be represented by the equality eN k = eP p eNP l ; where p = k div NP and l = k mod NP . In the above identity, the index of vector basis eP p is associated with the processor index on which element A(k) is located after being distributed using a BLOCK distribution.... ..."

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### Table 1, i.e. k = PBc + Bp + b and l = Bc + b. The distribution basis for a multi-dimensional array can be expressed as a tensor product of the distribution bases for each dimension.

1994

"... In PAGE 5: ...Table1 : Index mapping functions for regular data distributions. BLOCK CYCLIC CYCLIC(b) local to global k = p(dN=Pe) + l k = lP + p k = (l div b)bP + bp + l mod b global to local l = k mod dN=Pe l = k div P l = (k div Pb)b + k mod b global to proc p = k div dN=Pe p = k mod P p = (k div b) mod P k global index 0 k N ? 1; l local index 0 l lt; db ?dN=(Pb)e ; p processor 0 p lt; P.... In PAGE 5: ... Techniques developed in [11] can be used for the array redistribution in the general case. For identity alignments, the relationships between the global index, the local index and the processor index for regular data distributions of a one-dimensional array are shown in Table1 . The indexing for arrays A and A loc begins at zero and the processors are numbered from 0 to P ? 1.... In PAGE 8: ... For example, under a BLOCK distribution the array is partitioned into segments of size NP . The relationship between the global index k, the processor index p, and the local index l as shown in Table1 can be represented by the equality eN k = eP p eNP l ; where p = k div NP and l = k mod NP . In the above identity, the index of vector basis eP p is associated with the processor index on which element A(k) is located after being distributed using a BLOCK distribution.... ..."

Cited by 8