### Table 1. The truth table for the output signals of the VME bus controller example (the order of signals in the binary encodings is: dsr,

2004

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### Table 1. The truth table for the output signals of the VME bus controller example (the order of signals in the binary encodings is: dsr,

### Table II. Here, three linear output neurons are used in order to enable binary coding. Every output signal is then converted into binary digits as shown. Table III represents the data describing the new ANN used for diagnosis.

### Table III. One further signal is derived from the strace logs once they had been gathered. In [14] a classification of syscalls based on the threat they pose to system security is given. Syscalls are classified as belonging to one of four levels, level 1 being the most dangerous and level 4 the least, with a number of subgroupings within each level. We implemented this by generating a binary signal whenever a syscall which belonged to level 1 is observed.

### Table 1: Signal quality value conversion.

"... In PAGE 28: ...5 PACKET SCHEDULING IN WIRELESS NETWORK The conversion Table1 shows the quantified signal quality value and correspond- ing binary value. Column two shows the binary signal value included in the TTL- field bits two to five.... ..."

### Table 9: VT1,3-

"... In PAGE 5: ...able 8: VT1,3-Binary signals used as interruption...............................................................................52 Table9 : VT1,3-.... ..."

### Table 9: VT1,3-

"... In PAGE 5: ...able 8: VT1,3-Binary signals used as interruption..........................................................................52 Table9 : VT1,3- .... ..."

### Table 1: Fitness of the best individual after 100,000 function evaluations, for approximation of signal 1, using binary and real-number operators, and a population size of 100. Results averaged over 50 runs.

"... In PAGE 13: ...2.1 Mutation rate For a population of 100 individuals, using binary4 and real-number5 operators, and limiting the number of function evaluations to 100,000, we obtain the results shown in Table1 . This table contains the fitness (the relative L2 norm of the error) of the best individual found after 100,000 evaluations, averaged over 50 runs of the algorithm.... In PAGE 16: ...hlenbein, 1992), see Sect. 5.2.1) ensures that these parameter settings are close to the true optimum. In any case, from both Table1 and Table 2 we may infer that the use of real-number operators yields slightly better approximation results: the 95% confidence intervals do not overlap. This is illustrated in Fig.... ..."

### Table 2: Fitness of the best individual after 100,000 function evaluations, for approximation of signal 1, using binary and real-number operators, and mutation rates of 0.002 and 0.05, respectively. Results averaged over 50 runs.

"... In PAGE 13: ...utation rate of 0.002, and for the algorithm with real-number operators, we use a rate of 0.05. Both these figures are obtained from the results given in the previous section. The results obtained are given in Table2 , which contains the fitness (the relative L2 error) of the best individual found after 100,000 function evaluations, averaged over 50 runs of the algorithm. Fig.... In PAGE 16: ...hlenbein, 1992), see Sect. 5.2.1) ensures that these parameter settings are close to the true optimum. In any case, from both Table 1 and Table2 we may infer that the use of real-number operators yields slightly better approximation results: the 95% confidence intervals do not overlap. This is illustrated in Fig.... ..."