### Table 1. Numerical results obtained with solution technique 1.

"... In PAGE 7: ... In summary, we use three different approaches to the same problem. Results are reported in Table1 , Table 2, and Table 3, respectively. For each computed solution, a numerical integration using a Runge-Kutta scheme is carried out using a control evaluated over a fine grid.... ..."

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### Table 4.2: Numerical experiment using the reflection technique.

### TABLE II COMPUTATIONAL COMPLEXITY, ASSUMING g SHS IS A DIAGONAL MATRIX. WE HAVE OMITTED THE COMPLEXITY RELATED TO UPDATING ^ F AS IT DEPENDS ON THE SPECIFIC NUMERICAL TECHNIQUE USED TO SOLVE (40).

2006

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### Table 2: Computational complexity, assuming tildewidest SHS is a diagonal matrix. We have omitted the complexity related to updating F as it depends on the specific numerical technique used to solve (36).

### Table 2: Natural frequencies of tandem-axle truck Di erent numerical techniques have been considered for this analysis and, nally, the modi ed Gauss-Jordan numerical method has been preferably employed due to its rather fast and accurate convergence.

### Table 2. Numerical results obtained with solution technique 3 using 4 first order differential equations.

"... In PAGE 7: ... In summary, we use three different approaches to the same problem. Results are reported in Table 1, Table2 , and Table 3, respectively. For each computed solution, a numerical integration using a Runge-Kutta scheme is carried out using a control evaluated over a fine grid.... ..."

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### Table 2: Numerical results from solving the coating matrices by the multi-level block ILU preconditioning technique.

1999

"... In PAGE 7: ... Convergence was achieved when the 2-norm residual was reduced by 7 orders of magnitude. Table2 lists some statistics of the computations and the parameters used. In Table 2 and in all other tables followed, \iter.... In PAGE 7: ... Table 2 lists some statistics of the computations and the parameters used. In Table2 and in all other tables followed, \iter. quot; denotes the number of preconditioned iterations, \fact.... In PAGE 8: ... In some tables we use \{ quot; to indicate a lack of convergence. The results in Table2 show that our preconditioned iterative solver converged fast for solving the given matrices with the chosen parameters. We mention that, once the parameter quot; was chosen, the choices of the other parameters were not very critical in terms of achieving successful convergence, except in the case for solving the BKNIFE-01 matrix.... In PAGE 8: ...Table 2: Numerical results from solving the coating matrices by the multi-level block ILU preconditioning technique. Table 3 shows the number of the rows of the matrix (Schur complements) with zero diagonal values at each level, corresponding to the parameters listed in Table2 . We see that the original matrices contain a substantial number of rows with zero diagonal elements.... In PAGE 10: ... It can be seen that the multi-level block ILU preconditioner with a diagonal threshold strategy actually used less memory to achieve faster convergence rates than that yielded by the same preconditioner without a diagonal threshold strategy. Figure 5 shows the convergence history of the multi-level block ILU preconditioner for solving the PDF-1 matrix with di erent diagonal threshold tolerance , the other parameters were chosen the same as those used in Table2 . We see the suitable values of for this test problem are between 0:1 and 0:05.... ..."

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