### Table 4: Faultload characteristics #28under the #5CClarkNet9:1 quot; workload#29. Because of the exponential complex-

2002

"... In PAGE 18: ... First we provide more detailed description about our fault- loads and workloads. To gain insights into the properties of our faultloads, in Table4 wecharacterize our faultloads based on several aspects #28as discussed in Section 7#29 that a#0Bect the running time of the algorithm. The #0Crst two workloads we use are based on the ClarkNet web client trace #5B8#5D, which logs client machine names and access time to the ClarkNet WWW server.... ..."

Cited by 20

### Table 6: Complexity of multi-exponentiation using signed representations, d = 3

2002

### Tables grow exponentially in size with the number and/or complexity of the patterns, but real patterns are always small, so the performance of the process will not be a major issue.

### Table 3 gives the results from experiments with Gabor wavelets. The optimal frequency for the modulating complex exponential was found to be f =0.021 fs, where fs is the sampling frequency in rad/pixel.

2004

"... In PAGE 4: ... ACKNOWLEDGEMENTS The authors are grateful to Jon Miles at Miles Research [7] for providing the iris image database used in this study. Table3 . Results using Gabor wavelets of frequency f.... ..."

Cited by 2

### Table 2. Checks and verification Here, the problem of space and time complexity of the finite state machines (automata) for recognizing languages arises. In general, the classical regular language operators (concatenation, alternative, repetition) do not introduce any exponential growth of the state space of a parsing finite state automaton. However, behavior protocols employ also the and- parallel, composition, and adjustment operators that introduce exponential complexity of the resulting automata which might lead to the state explosion problem. In fact, the composition and adjustment operators behave better than the and-parallel operator in terms of the required state space as they comprise synchronization of events, thus reducing the interleaving of traces.

2002

Cited by 112

### Table 1. The table gives estimates of the complexity, without and with optimization, of the prover and verifier in terms of general exponentiations in Gq for some common security parameters.

"... In PAGE 29: ... Each function veriStepi computes the complexity of verifier in the ith step of the protocol and correspondingly for proStepi. In Table1 we give the complexity for some common parameters.... ..."

### Table 1: Characteristics of given jobs in the example sult in an exponential problem that could not be solved in reasonable time. Further complexity arises from interactions between the four furnaces which cannot be discussed in this paper.

1991