Search results for "Algorithm"
showing 10 items of 4887 documents
An efficient distributed approach for dynamic multicast trees
2005
In this paper we present a distributed algorithm for constructing efficient multicast trees in large networks. The algorithm allows the set up of effective distribution trees using a coordination protocol among the network nodes. The algorithm has been implemented and extensively tested both in simulation, and on experimental networks. Performance evaluation indicates that our approach outperforms the state-of-the-art distributed algorithms for multicast tree setup, providing good levels of convergence time and communication complexity. Furthermore, we introduce a distributed technique for dynamically updating the multicast tree. The approach monitors the accumulated damage as nodes join or…
About the finite convergence of the proximal point algorithm
1988
We study the finite convergence property of the proximal point algorithm applied to the partial inverse, with respect to a subspace, of the subdifferential of a polyhedral convex function. Using examples we show how sufficient conditions providing the finite convergence can be realized and we give a case with non finite termination.
A Constructive Arboricity Approximation Scheme
2020
The arboricity \(\varGamma \) of a graph is the minimum number of forests its edge set can be partitioned into. Previous approximation schemes were nonconstructive, i.e., they approximate the arboricity as a value without computing a corresponding forest partition. This is because they operate on pseudoforest partitions or the dual problem of finding dense subgraphs.
On the collision property of chaotic iterations based post-treatments over cryptographic pseudorandom number generators
2018
International audience; There is not a proper mathematical definition of chaos, we have instead a quite big amount of definitions, each of one describes chaos in a more or less general context. Taking in account this, it is clear why it is hard to design an algorithm that produce random numbers, a kind of algorithm that could have plenty of concrete appliceautifat (anul)d bions. However we must use a finite state machine (e.g. a laptop) to produce such a sequence of random numbers, thus it is convenient, for obvious reasons, to redefine those aimed sequences as pseudorandom; also problems arise with floating point arithmetic if one wants to recover some real chaotic property (i.e. propertie…
Domain Generation Algorithm Detection Using Machine Learning Methods
2018
A botnet is a network of private computers infected with malicious software and controlled as a group without the knowledge of the owners. Botnets are used by cybercriminals for various malicious activities, such as stealing sensitive data, sending spam, launching Distributed Denial of Service (DDoS) attacks, etc. A Command and Control (C&C) server sends commands to the compromised hosts to execute those malicious activities. In order to avoid detection, recent botnets such as Conficker, Zeus, and Cryptolocker apply a technique called Domain-Fluxing or Domain Name Generation Algorithms (DGA), in which the infected bot periodically generates and tries to resolve a large number of pseudorando…
Study on the Effects of Pseudorandom Generation Quality on the Performance of Differential Evolution
2011
Experiences in the field of Monte Carlo methods indicate that the quality of a random number generator is exceedingly significant for obtaining good results. This result has not been demonstrated in the field of evolutionary optimization, and many practitioners of the field assume that the choice of the generator is superfluous and fail to document this aspect of their algorithm. In this paper, we demonstrate empirically that the requirement of high quality generator does not hold in the case of Differential Evolution.
Considerations on correlations in shift-register pseudorandom number generators and their removal
1997
Abstract We present a simple calculation quantitatively explaining the triplet correlations in the popular shift-register random number generator “R250”, which were recently observed numerically by Schmid and Wilding, and are known from general analysis of this type of generator. Starting from these considerations, we discuss various methods to remove these correlations by combining different shift-register generators. We implement and test a particularly simple and fast version, based on an XOR combination of two independent shift-register generators with different time lags. The results indicate that this generator has much better statistical properties than R250, while being only a facto…
Parallelization of the Wolff single-cluster algorithm.
2010
A parallel [open multiprocessing (OpenMP)] implementation of the Wolff single-cluster algorithm has been developed and tested for the three-dimensional (3D) Ising model. The developed procedure is generalizable to other lattice spin models and its effectiveness depends on the specific application at hand. The applicability of the developed methodology is discussed in the context of the applications, where a sophisticated shuffling scheme is used to generate pseudorandom numbers of high quality, and an iterative method is applied to find the critical temperature of the 3D Ising model with a great accuracy. For the lattice with linear size L=1024, we have reached the speedup about 1.79 times …
On the genetics of psoriasis
1973
To elucidate the mode of inheritance in psoriasis, Falconer's model for estimating heritability which is under the assumption of multifactorial inheritance, was applied to the data of Hellgren (1967) from Sweden. The heritability estimates were based on both manifest and potential psoriasis since a clear separation of these two categories was impossible. These estimates were 64% for parents, 60% for siblings and 52% for all first degree relatives which included the children of psoriatic cases. For second degree relatives it was 48%. None of these differences are statistically significant. The results are discussed.
Small-sample characterization of stochastic approximation staircases in forced-choice adaptive threshold estimation
2007
Despite the widespread use of up—down staircases in adaptive threshold estimation, their efficiency and usability in forced-choice experiments has been recently debated. In this study, simulation techniques were used to determine the small-sample convergence properties of stochastic approximation (SA) staircases as a function of several experimental parameters. We found that satisfying some general requirements (use of the accelerated SA algorithm, clear suprathreshold initial stimulus intensity, large initial step size) the convergence was accurate independently of the spread of the underlying psychometric function. SA staircases were also reliable for targeting percent-correct levels far …