ABSTRCT: Use CFD method to study of the air distribution of certain practical project. By using three-dimensional RNG k-εturbulent model, the air distribution of an underground main workshop in hydropower station with heat source at non-isothermal condition has been designed by means of numerical simulation. Solve the controlling equations by using the soft ware of computational fluid dynamics ...

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 ...

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...

BACKGROUND Deep brain stimulation of the subthalamic nucleus (STN DBS) ameliorates the motor symptoms of Parkinson's disease (PD). However, some aspects of executive control are impaired with STN DBS. OBJECTIVE We tested the prediction that (i) STN DBS interferes with switching from automatic to controlled processing during fast-paced random number generation (RNG) (ii) STN DBS-induced cognit...

Operating systems and applications rely on random number generators (RNGs) for a number of important tasks, most notably cryptographic key generation. The impact of flawed random number generation practices has been studied extensively in the past [2, 5]. In this paper, we examine the implications of an RNG bug in FreeBSD that was fixed by Subversion commit r278907 [3]. In particular, our analy...