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if (weather != "sun") { bringUmbrella(); }
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This statement brings an umbrella if it is not sunny outside. Another way of writing this would be to use the not operator to negate an equality:
if (!(weather == "sun")) { bringUmbrella(); }
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First, we provide an intuitive description of the meet-in-the-middle attack. Then we consider a more efficient implementation. Suppose that from the A table, we have uniquely determined T(w), ( b ) , T T ( c ) ,and T ( d ) , for some a , b, c, and d. Then for each of the 232 choices for (KO,K1, K2, K 3 ) , we compute
This line of code functions identically to the one earlier. Because the not operator binds very tightly (it has a high precedence in the order of operations), you have to use parentheses. Otherwise, the expression !weather == "sun" evaluates whether not-weather is equal to sun.
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the signal/noise ratio for the hypothesis H0 ; is the interference variance. When the level of interference is relatively low, e.g. at q0 10 dB, the criterion of Equation (22.29) coincides with that in Equation (22.19). The dependency between the Fisher criterion Equation (22.29) and the signal/noise ratio q0 is shown in Figure 22.2. We find from Equations (22.29) (22.32) and Figure 22.2 that the recognition effectiveness of the proposed approach, as well as the recognition effectiveness of the Hartley approach, depends only on the difference of the signal variances and the signal/noise ratio. It can be seen from Equations (22.29) (22.32) and Figure 22.2 that the effectiveness of the proposed approach and the Hartley, cosine and PSD approaches decreases with decrements of the signal/noise ratio q0 (e.g. increments of the noise variance) for arbitrary values of the parameter b; however, the use of the proposed approach in the considered noisy environment provides the same recognition effectiveness gain (see Equations (22.30) and (22.31) as in the case without a noisy environment.
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and similarly for b, c, and d. Then we store R = ( R ( a ) , R ( b ) , R ( c ) , R ( d ) ) and the putative key bytes ( K OK1, K2, K3) in a row of a table M . Then M , has 232 rows, which we sort on R. Next, we work backwards from the T ( a ) ,T ( b ) , ( c ) ,and T ( d ) ,searching T for a matching R in the table. More precisely, for each = ( K 4 ,K5, K6, K7), I we find all pairs ( S( u ), R( ) ) , such that a
If you want to act on a combination of conditions, you might try nesting or duplicating your if statements together like this:
if (weather == "rain") { bringUmbrella(); } if (weather == "sleet") { bringUmbrella(); } if (weather == "snow") { bringUmbrella(); }
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