### TABLE III FUZZY TRIANGULAR CONORMS (T-CONORM) [5].

### Table 1. Some well-known triangular norms (T-norms) and triangular conorms (T- conorms)

"... In PAGE 5: ...In fuzzy logic, triangular norms (roughly the equivalent of AND operations) and triangular co-norms (roughly the equivalent of OR operations) are used to represent the intersection and the union of two fuzzy sets, respectively. Some well-known triangular norms together with their dual triangular co-norm are shown in Table1 . From all possible triangular norms the minimum norm is the largest and the weak norm (Table 1) is the smallest.... In PAGE 5: ... Some well-known triangular norms together with their dual triangular co-norm are shown in Table 1. From all possible triangular norms the minimum norm is the largest and the weak norm ( Table1 ) is the smallest. From all possible triangular conorms the strong norm is the largest and the maximum norm (Table 1) is the smallest.... In PAGE 5: ... From all possible triangular norms the minimum norm is the largest and the weak norm (Table 1) is the smallest. From all possible triangular conorms the strong norm is the largest and the maximum norm ( Table1 ) is the smallest. We have chosen for a t-norm (with his dual conorm) which is situated between those two extremes, i.... ..."

### Table 3 Average Expenditure, Poverty, and Inequality in Mozambique by Province Province Survey Estimate Census-Based Estimate Mean Expenditure Headcount Index Gini Coefficient Mean Expenditure Headcount Index Gini Coefficient

2003

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### Table 2 Average Expenditure, Poverty, and Inequality in Madagascar by Province amp; Sector Province Survey Estimate Census-Based Estimate Mean Expenditure Headcount Index Gini Coefficient Mean Expenditure Headcount Index Gini Coefficient

2003

Cited by 2

### Table 4: Edit Distance based on Transducers with Weighted Automata

"... In PAGE 11: ...1. Applying the approach on the acyclic automata of the sample data set results in the distance values contained in Table4 . The table contains only the upper triangular matrix to improve the readability.... In PAGE 14: ...approach based on weighted automata turns out to provide a distance measure which pro- vides only a coarse grained differentiation of automata (see Table4 ). However, the n-gram based approach (see Table 5) has two major draw backs: it requires high computational effort in case of automata with complex cycles, that is, at least two cycles in an automaton share at least a single state.... ..."

### Table 3: Prototypical norms and conorms.

### Table 6: Distributed Weights vs Standard Weights

1996

"... In PAGE 15: ... The use of this technique improved the rate at which the neural network converged on a solution. Table6 shows the di erence between the use of the distributed output weights, row one, and the the standard output weights, row two, in terms of training performance based on cross validation, mean squared error and number of epochs as de ned in 2.... ..."

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### Table 2 Computational results for the engine component. The columns have the following meanings. Weights (Yes/No) refers to whether or not node weights based on element types were used. P: the number of processors. Iterations: total number of FETI iterations for 31 linear solves. Project: Time spent (seconds) in projecting the right- hand sides Precond: Time spent (seconds) in applying the Dirichlet preconditioner. Orth: Time spent (seconds) in reorthogonalizing the CG direction vectors. Op: The time spent (seconds) back-solving the coarse grid and subdomain linear systems.

"... In PAGE 14: ... The weights are 3, 4, and 3 for the for the hexagonal, prismatic, and triangular elements respec- tively. Detailed timing information is displayed in Table2 . The difference between the Total time and the sums of the individual times is of course the time spent on other tasks.... In PAGE 15: ...5e+6 9 30 28 120 195 Table 3 Computational results for the aerospace component. The columns have the same meanings as in Table2 . The additional column Nnz reports the maximum number of nonzeros in the factor of a subdomain stiffness matrix.... ..."

### Table 2 Variable Means, All Years*

2004

"... In PAGE 10: ... Females may have a higher propensity to stay at a home institution due to family obligations, or conversely, family obligations might cause a female faculty member to leave the labor market. Table2 presents the means of all of these variables, in both the constant and variable dataset, based on form of institutional control, for all observations and years in this study. Over time, the yearly weighted averages of the time sensitive variables either remained remarkably constant (TEN) or demonstrated a steady, unwavering increase (COMP, FEM) within their sample and form of control, with the absolute differences between the public and private aggregates remaining steady as well.... ..."

### Table 1: Average date of the surveys used for each reference year

2004

"... In PAGE 8: ... Indeed, our estimates for the early 1980s rely heavily on projections based on distributions for the late 1980s. Table1 gives the average survey year by region for each reference year. While Africa is clearly the region in which survey coverage has most improved when compared to our past estimates (Chen and Ravallion, 2001), the weakness of our coverage of Africa should be kept in mind when interpreting our results.... ..."

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