Complex network classification using partially self-avoiding deterministic walks

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

Numerical study of Mach number and thermal effects on sound radiation by a mixing layer

Mach number and thermal effects on the mechanisms of sound generation and propagation are investigated in spatially evolving two-dimensional isothermal and non-isothermal mixing layers at Mach number ranging from 0.2 to 0.4 and Reynolds number of 400. A characteristic-based formulation is used to solve by direct numerical simulation the compressible Navier-Stokes equations using high-order schemes. The radiated sound is directly computed in a domain that includes both the near-field aerodynamic source region and the far-field sound propagation. In the isothermal mixing layer, Mach number effects may be identified in the acoustic field through an increase of the directivity associated with the non-compactness of the acoustic sources. Baroclinic instability effects may be recognized in the non-isothermal mixing layer, as the presence of counter-rotating vorticity layers, the resulting acoustic sources being found less efficient. An analysis based on the acoustic analogy shows that the directivity increase with the Mach number can be associated with the emergence of density fluctuations of weak amplitude but very efficient in terms of noise generation at shallow angle. This influence, combined with convection and refraction effects, is found to shape the acoustic wavefront pattern depending on the Mach number.

Thermal alteration and morphological changes of sound and demineralized primary dentin after Er:YAG laser ablation

The purpose of this study was to assess the influence of Er:YAG laser pulse repetition rate on the thermal alterations occurring during laser ablation of sound and demineralized primary dentin. The morphological changes at the lased areas were examined by scanning electronic microscopy (SEM). To this end, 60 fragments of 30 sound primary molars were selected and randomly assigned to two groups (n = 30); namely A sound dentin (control) and B demineralized dentin. Each group was divided into three subgroups (n = 10) according to the employed laser frequencies: I4 Hz; II6 Hz, and III10 Hz. Specimens in group B were submitted to a pH-cycling regimen for 21 consecutive days. The irradiation was performed with a 250 mJ pulse energy in the noncontact and focused mode, in the presence of a fine water mist at 1.5 mL/min, for 15 s. The measured temperature was recorded by type K thermocouples adapted to the dentin wall relative to the pulp chamber. Three samples of each group were analyzed by SEM. The data were submitted to the nonparametric Kruskal-Wallis test and to qualitative SEM analysis. The results revealed that the temperature increase did not promote any damage to the dental structure. Data analysis demonstrated that in group A, there was a statistically significant difference among all the subgroups and the temperature rise was directly proportional to the increase in frequency. In group B, there was no difference between subgroup I and II in terms of temperature. The superficial dentin observed by SEM displayed irregularities that augmented with rising frequency, both in sound and demineralized tissues. In conclusion, temperature rise and morphological alterations are directly related to frequency increment in both demineralized and sound dentin. Microsc. Res. Tech., 2011. (c) 2011 Wiley Periodicals, Inc.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.

Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.