We present a first random number generator (RNG) which simultaneously uses independent spatial and temporal quantum randomness contained in an optical system. Availability of the two independent sources of entropy makes the RNG resilient to hardware failure and signal injection attacks. We show that the deviation from randomness of the generated numbers can be estimated quickly from simple meas...

Prototype-based clustering algorithms such as the Self Organizing Map (SOM) or Neural Gas (NG) offer powerful tools for automated data inspection. The distribution of prototypes, however, does not coincide with the underlying data distribution and magnification control is necessary to obtain information theoretic optimum maps. Recently, several extensions of SOM and NG to general non-vectorial ...

This study investigates experimentally and numerically the effects of sills with different geometric specifications at various positions on hydraulic characteristics flow through sluice gates. The simulation results showed that RNG turbulence model’s statistical indicators yield high accuracy compared to k-?, k-?, LES models. discharge coefficient (Cd) has an inverse relationship gate opening. ...

The Yakhot and Orszag RNG theory of turbulence has generated a number of scaling law constants in reasonable quantitative agreement with experiments. The theory itself is highly mathematical, and its assumptions and approximations are not easily appreciated, particularly since several rather unconventional artifices are employed. The present paper reviews the RNG theory and recasts it in more c...

Existing symmetric encryption algorithms target messages consisting of elementary binary blocks of at least 64 bits. Some applications need a block cipher which operates over smaller and possibly nonbinary blocks, which can be viewed as a pseudo-random permutation of n elements. We present an algorithm for selecting such a random permutation of n elements and evaluating efficiently the permutat...

Let i, n be elements of N. The functor proj(i, n) yielding a function from Rn into R is defined by: (Def. 1) For every element x of Rn holds (proj(i, n))(x) = x(i). Next we state two propositions: (1) dom proj(1, 1) = R1 and rng proj(1, 1) = R and for every element x of R holds (proj(1, 1))(〈x〉) = x and (proj(1, 1))−1(x) = 〈x〉. (2)(i) (proj(1, 1))−1 is a function from R into R1, (ii) (proj(1, 1...