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this.year = year; } public function toString():String { return " + title + ", + author + ( + year + ) ; } }
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When computing a modular exponentiation ud (mod N ) using the CRT approach, we first compute ad, (mod p ) using the repeated squaring algorithm in Table (7.7), where d, = d (mod ( p - 1)). Suppose that when computing u d p (mod p ) , we have ko multiply steps and kl squaring steps. Note that ko and kl depend only on d, and, therefore, only on d and p , and not on a. Since the probability (7.21) holds for each multiply, and the probability (7.22) holds for each square, the expected number of extra reductions is a (mod p ) P (7.23) +k1-. IC0 2R 3R As a function of a , the expression in (7.23) is piecewise linear-more precisely, it is a linear function with discontinuities a t integer multiples of p . Qualitatively, the graph of (7.23) is similar to that in Figure 7.2 (see Problem 2). Note that the total number of extra reductions in the calculation of Cd (mod N) also include extra reductions due to the factor q. Nevertheless, there would still be a discontinuity in the total number of extra reductions at every integer multiple of p (and also q ) .
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where r is the cardinality of R (i.e. the number of pairs in binary relation R), d is the cardinality of the domain of R and c is the cardinality of the range of R. Note that the quantity r/dc provides a measure of the density of the relation R. The quantity r d + c is a measure of the economy of information.
You ll add onto this example in the method ch8ex6(), after the data has been created. So far you should simply see the bookshelf in the order you created it:
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Figure 7.2: Expected number of extra reductions. The idea behind Schindler s timing attack follows directly from the graph in Figure 7.2. Suppose we select ciphertexts CO and C1, with Co < C1. Let T(Co)and T(C1)be the timing measurements for the decryption of Co and C1, respectively. Assuming that timing differences are dominated by the number of extra reductions, we would generally expect T(C1)- T(C0)to be relatively small, since the number of extra reductions grows slowly (linearly) from Co to C1. However, suppose that Co and C1 bracket a multiple of p . For example, suppose that we have Co = 2 p - k and C = 2p l , where k and are 1 reasonably small. Then due to the discontinuity in the number of extra reductions at 2p, the expected difference T(Co)- T(C1)would be relativcly large. Therefore, we can select an initial value z and an offset A and let
Now armed with a set of data, you can explore the sorting functions, starting with the sort() method. Using sort() with no additional parameters sorts the items in the default manner: alphabetically based on the object s string value. Because you ve de ned the toString() method for the Book class to print the book title, then author, then date, you should see the list sorted alphabetically by title. This isn t because the code is sorting by the title per se, but merely because those letters come rst in the string representation of the book. The following code:
bookshelf.sort();
+ PA,
Vectorization is a process that finds the vectors (such as straight lines, arcs and circles) from the raster images. Much research work on this area has been done, and many vectorization methods and their software have been developed. Although the vectorization for the lexical phase is more
reorders the array to produce this order:
"Anathem", Neal Stephenson (2008) "Jonathan Strange & Mr Norrell", Susanna Clarke (2006) "The Crystal World", J.G. Ballard (1966) "VALIS", Philip K. Dick (1991)
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