### Table IX. Two pairs of T-operators

in Building multi-way decision trees with numerical attributes, Technical report available upon request

2001

Cited by 2

### Table 1. Best solutions found with different strategies. Third row shows the SHA-EA using mu- tation (M) and crossover (C) operations, but without using simple transposition (T) operation.

"... In PAGE 1: ... We used a population of 100 individual for binary functions and 200 for real val- ued functions, using 32 bits for encoding each real value. Table1 , compares the results obtained by SHA-EA with some reported results in the literature. 2 Conclusions We presented a simplified version of the adaptive evolutionary algorithm proposed by Gomez and Dasgupta [1].... ..."

### Table 3: More results on the Mae-West for March 2002. all children of x in T. This operation requires constant time if labels are stored using pointers (to the parent nodes). We also mention that our approach may have a further bene t: assume that changes occur in the routing table with roughly a uniform distribution over all entries. Then, we would expect much more changes in the \simple quot; table containing all leaves. Therefore, the forwarding table corresponding to the other subtable can be optimize more for the lookup operation, rather than for the e cient update. At the present state of our research we do not know whether the assumption on the uniform distribution of changes is realistic; however, by looking at the number of entries having a subtree of a given height only (e.g., leaves have subtree of height equal 0), this assumption seems to be reasonable (see Table 5).

2003

Cited by 1

### Table 2: A complete set of transform operators

"... In PAGE 3: ... It is not hard to construct a set of transform operators that is complete in the sense that they can be combined to convert any task expression into any other. One approach is to mirror the recursive definitions by which compound tasks are constructed, as shown in Table2 . Each transform is reversible.... In PAGE 3: ...Table 2: A complete set of transform operators The set shown in Table2 is complete, since any task expression must be built following the constructs in Table 1, and for each construct we can find a corresponding transform in Table 2. The operators are reversible, and therefore can be used to transform any task expression to [noop:] and then transform [noop:] to any other task expression.... In PAGE 3: ...Table 2: A complete set of transform operators The set shown in Table 2 is complete, since any task expression must be built following the constructs in Table 1, and for each construct we can find a corresponding transform in Table2 . The operators are reversible, and therefore can be used to transform any task expression to [noop:] and then transform [noop:] to any other task expression.... In PAGE 5: ... Template ambiguity is an important property of a set of instruction templates in its own right, and it also affects efficiency described below. Coverage We measure coverage by the proportion of transforms in a complete set, for example Table2 , that can be addressed by instruction templates. In terms of syntactic transform operators, our set of instruction templates described in the previous section does not provide complete coverage.... In PAGE 5: ... For example, there is no reliable way to transform from [seq: t] to the operationally equivalent t using the instruction templates defined. However, all of the transforms from Table2 are covered by transforms from the instruction templates up to purely syntactic differences, so this set provides complete coverage. Efficiency Two measures are used to capture the efficiency of a set of instruction templates.... In PAGE 5: ... Since [2] has template ambiguity, we increase the count to 4, essentially positing a copy of [2] that is only used for existing tasks and one that is only used for new tasks. Our reference set of transform operators from Table2 has 9 operators, yielding a coverage efficiency of 9/4, or 9/5 if template [3] is included. Roughly half as many templates are required as operators for two reasons.... ..."

### Table 7. Reverse multicast ____________________________________________ Reverse Multicast ___________________________________ System

1990

Cited by 1

### Table II. The default reversible transformation is

2000

Cited by 92

### Table 3: LISREL Estimates, Standard Errors for Confirmatory Factor Analysis and Item Means with Response Modes

in The Relationship between Educational Ideologies and Technology Acceptance in Pre-service Teachers

"... In PAGE 7: ... The questions in the Table 2 represent the three factors of technology acceptance. Table3 indicates the Lambda-x estimates and standard errors as obtained for each of the observed variables from the confirmatory factor analysis, with their abbreviations, the names of the latent variables, response modes, and respective item means. Lambda-x values, which are the loadings of each observed variable on the respective latent variable, indicate reasonable sizes to support the idea of using these latent variables in the proposed path analytic model to explain significant factors in educational technology acceptance.... ..."

### Table 2. Reversed predictions by method

"... In PAGE 4: ... Table2 shows the results of applying the methodology as follows. The first column shows the percentage of reversed projects out of the twelve projects studied.... In PAGE 5: ... It does not seem realistic to expect that users will be able to reverse eleven aspects in a project. To analyze the methods that individualize each project (last three in Table2 ), we revised our methodology to allow these methods to use their knowledge to guide their reversal strategy. These methods indeed have the ability to use embedded knowledge to reverse only the values that are not supportive of success.... ..."

### Table 3: Reversibility of atomic operations

"... In PAGE 3: ... The commands for map construction have been carefully designed in such a way that all of them are invertible. Indeed, each atomic operation has its reverse atomic operation (see Table3 ), and therefore the resulting complex operations are reversible. Map command Decomposition Reverse Move a point N Move a point Add a point SN Delete a point Delete a point NM Add a point Add a line SNSLN Delete a line Delete a line NUMNM Add a line Join 2 points SLNM Unjoin 2 points Unjoin 2 points SNUM Join 2 points Join point+line SLONSLNM Unjoin pt+line Unjoin pt+line SNUMNRUM Join pt+line Join 2 lines SLONSLONSL NM Unjoin 2 lines Unjoin 2 lines SNUMNRUM NRUM Join 2 lines Table 2: The map commands and their decomposition Reversibility of the operations on the dynamic spatio- temporal Voronoi data structure Overall reversibility of the Voronoi spatial data structure, as for any system, depends upon the fact that reversible primitives are reversibly composed in order to get complex operations (see [Baker92a]).... ..."