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The handoff rate is identified in a hybrid channel allocation algorithm of a wireless and mobile network. In this network model, both new calls and handoff calls to a cell have possibilities to borrow channels from the control center if all allocated channels to the cell are used up. In addition, there is a buffer with finite size reserved exclusively for handoff calls in a cell when they arrived but are not be able to borrow channels from the control center. In this paper, we derived a novel and theoretical expression of the handoff rate in the network first. This analytical expression for handoff rate is a general form which covers several special cases discussed in the literature. Then, an efficient iterative algorithm to calculate this handoff rate is proposed also. By using this algorithm, the handoff rate and the blocking probability of both new calls and handoff calls will be successfully derived at the same time. Furthermore, our numerical analysis validates the algorithm and the corresponding theoretic expression. [ABSTRACT FROM AUTHOR]

An "r-consecutive-k-out-of-n: F system" consists of n linearly or cyclically ordered components. The system fails if and only if at least r nonoverlapping sequences of k consecutive components fail. In this paper, we give recursive formulas to compute the reliability of circular "r-consecutive-k-out-of-n: F system" in general case. More precisely, our goal in the present paper is to give formulas to evaluate the reliability of the circular "r-consecutive-k-out-of-n: F system" via those of a linear one. [ABSTRACT FROM AUTHOR]

Differential privacy becomes a standard for evaluating the privacy protection performance for an algorithm these years. However, the definition of differential privacy seems not so easy to understand as the classical k-anonymity and etc. In this paper, we propose a new measure which is more comprehensible. Some properties of such measure are investigated and the relationship between our new definition and differential privacy is studied. [ABSTRACT FROM AUTHOR]

Probably the simplest and most frequently used way to illustrate the power of quantum computing is to solve the so-called Deutsch's problem. Consider a Boolean function f: {0,1} → {0,1} and suppose that we have a (classical) black box to compute it. The problem asks whether f is constant [that is, f(0) = f(1)] or balanced [f(0) ≠ f(1)]. Classically, to solve the problem seems to require the computation of f(0) and f(1), and then the comparison of results. Is it possible to solve the problem with only one query on f? In a famous paper published in 1985, Deutsch posed the problem and obtained a "quantum" partial affirmative answer. In 1998, a complete, probability-one solution was presented by Cleve, Ekert, Macchiavello and Mosca. Here we will show that the quantum solution can be de-quantized to a deterministic simpler solution which is as efficient as the quantum one. The use of "superposition," a key ingredient of quantum algorithm, is — in this specific case — classically available. [ABSTRACT FROM AUTHOR]

One of the major challenges facing real time world applications that employ Bayesian networks, is the design and development of efficient inference algorithms. In this paper we present an approximate real time inference algorithm for Bayesian Networks. The algorithm is an anytime reasoning method based on probabilistic inequalities, capable of handling fully and partially quantified Bayesian networks. In our method the accuracy of the results improve gradually as computation time increases, providing a trade-off between resource consumption and output quality. The method is tractable in providing the initial answers, as well as complete in the limiting case. [ABSTRACT FROM AUTHOR]

We introduce and discuss the recent Agrawal–Kayal–Saxena deterministic algorithm solving primality in polynomial time. [ABSTRACT FROM AUTHOR]

Link prediction based on random walks has been widely used. The existing random walk algorithms ignore the probability of a walker visit from the initial node to the destination node for the first time, which makes a major contribution to establish links in some networks. To deal with the problem, we develop a link prediction method named Local Random Walk with Distance (LRWD) based on local random walk and the shortest distance of node pairs. In LRWD, walkers walk with their own steps rather than uniform steps. To evaluate the performance of the LRWD algorithm, we present the concept of distance distribution. The experimental results show that LRWD can improve the prediction accuracy when the distance distribution of the network is relatively concentrated. [ABSTRACT FROM AUTHOR]

The critical points of the 3-states two-layer Potts model on square lattice for different interlayer couplings (Kx = Ky ≠ Kz) are calculated with high precision using probabilistic cellular automata with Glauber algorithm, where Kx and Ky are the nearest-neighbor interactions within each layer in the x- and y-directions respectively, and Kz is the interlayer coupling. The obtained results are 0.726, 0.807, 0.928, 0.987 and 1.00 for the cases Kz/Kx = 1, 0.5, 0.1, 0.01 and 0.001 respectively, from which the critical curve is been constructed based on this model. [ABSTRACT FROM AUTHOR]