نتایج جستجو برای: decomposed lifting algorithm dla
تعداد نتایج: 780082 فیلتر نتایج به سال:
Results from a modified Diffusion Limited Aggregation (DLA) model are presented. The modifications of the classical DLA model are in the attachment to the cluster rules and in the scheme of particle generation/killing. In the classical DLA model, if a particle reaches the growing cluster, it sticks to it immediately and irreversibly and then the next particle is released. We will abandon this o...
When factoring polynomials defined over Z[x], one computes the factors modulo m from the factors modulo p, where p is a suitable prime number and m a power of p, greater than rn, a bound on the absolute value of the coefficient of any factor of the polynomial. This is done using the Hensel lemma. We present a new way to perform this lifting process based on the idea of partial fraction decompos...
background : lifting methods, including standing stance and techniques have wide effects on spine loading and stability. previous studies explored lifting techniques in many biomechanical terms and documented changes in muscular and postural response of body as a function of techniques .however, the impact of standing stance and lifting technique on human musculoskeletal had not been investigat...
To address the conflicting requirements between holding specified surface quality and decreasing build time in layered manufacturing, we present a feature-based fabrication methodology whereby the curvature effects are localized within each decomposed volume. However, staircase interaction between the boundaries of the decomposed neighboring volumes creates geometric incompatibility for deposit...
Texture synthesis is an essential aspect in virtual reality, making it an important research area in recent years. A new texture synthesis algorithm is proposed in this paper. Using the Direction Empirical Mode Decomposition (DEMD), the inherent direction of the sample textures is calculated and the samples are decomposed into a series of images. Based on the feature value in the direction, eve...
We investigate diffusion-limited aggregation (DLA) in a wedge geometry. Arneodo and collaborators have suggested that the ensemble average of DLA cluster density should be close to the noise-free selected Saffman-Taylor finger. We show that a different, but related, ensemble average, that of the conformal maps associated with random clusters, yields a nontrivial shape which is also not far from...
I review current results from searching for galaxies giving rise to damped Lyα absorbers (DLAs) at z < 1. Using 14 confirmed DLA galaxies, I further show that intermediate-redshift galaxies possess large H I envelope out to 24−30 h kpc radius. The photometric and spectral properties of these galaxies confirm that DLA galaxies are drawn from the typical field population, and not from a separate ...
Many behavioural equivalences or preorders for probabilistic processes involve a lifting operation that turns a relation on states into a relation on distributions of states. We show that several existing proposals for lifting relations can be reconciled to be different presentations of essentially the same lifting operation. More interestingly, this lifting operation nicely corresponds to the ...
A major drawback of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is its high peak-to-average power ratio (PAPR). A decomposed selected mapping algorithm is proposed to overcome this problem. The candidate OFDM frames transmitted on antennas are decomposed to be real and imaginary part, thereby, a sufficiently large number of alternative transmit ...
Let f (x) be a separable polynomial over a local field. The Montes algorithm computes certain approximations to the different irreducible factors of f (x), with strong arithmetic properties. In this paper, we develop an algorithm to improve any one of these approximations, till a prescribed precision is attained. The most natural application of this ‘‘single-factor lifting’’ routine is to combi...
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