Research on benthic scene recognition using multi-scale self-similarity model and statistical analysis of increments

2007 ◽  
Author(s):  
Guoliang Yang ◽  
Fuyuan Peng ◽  
Xutao Li ◽  
Kun Zhao ◽  
Jingdong Chen
Keyword(s):  
Statistical Analysis ◽  
Scene Recognition ◽  
Self Similarity ◽  
Multi Scale ◽  
Similarity Model

scholarly journals Extended power-law scaling of air permeabilities measured on a block of tuff

2012 ◽  
Vol 16 (1) ◽  
pp. 29-42 ◽  
Author(s):  
M. Siena ◽  
A. Guadagnini ◽  
M. Riva ◽  
S. P. Neuman
Keyword(s):  
Power Law ◽  
Structure Functions ◽  
Self Similarity ◽  
Scaling Exponents ◽  
Multi Scale ◽  
Sample Structure ◽  
Heavy Tailed ◽  
Non Gaussian ◽  
Nonlinear Fashion ◽  
Extended Power

Abstract. We use three methods to identify power-law scaling of multi-scale log air permeability data collected by Tidwell and Wilson on the faces of a laboratory-scale block of Topopah Spring tuff: method of moments (M), Extended Self-Similarity (ESS) and a generalized version thereof (G-ESS). All three methods focus on q-th-order sample structure functions of absolute increments. Most such functions exhibit power-law scaling at best over a limited midrange of experimental separation scales, or lags, which are sometimes difficult to identify unambiguously by means of M. ESS and G-ESS extend this range in a way that renders power-law scaling easier to characterize. Our analysis confirms the superiority of ESS and G-ESS over M in identifying the scaling exponents, ξ(q), of corresponding structure functions of orders q, suggesting further that ESS is more reliable than G-ESS. The exponents vary in a nonlinear fashion with q as is typical of real or apparent multifractals. Our estimates of the Hurst scaling coefficient increase with support scale, implying a reduction in roughness (anti-persistence) of the log permeability field with measurement volume. The finding by Tidwell and Wilson that log permeabilities associated with all tip sizes can be characterized by stationary variogram models, coupled with our findings that log permeability increments associated with the smallest tip size are approximately Gaussian and those associated with all tip sizes scale show nonlinear variations in ξ(q) with q, are consistent with a view of these data as a sample from a truncated version (tfBm) of self-affine fractional Brownian motion (fBm). Since in theory the scaling exponents, ξ(q), of tfBm vary linearly with q we conclude that nonlinear scaling in our case is not an indication of multifractality but an artifact of sampling from tfBm. This allows us to explain theoretically how power-law scaling of our data, as well as of non-Gaussian heavy-tailed signals subordinated to tfBm, are extended by ESS. It further allows us to identify the functional form and estimate all parameters of the corresponding tfBm based on sample structure functions of first and second orders.

scholarly journals Self-similarity model of nonsingular perfect gas universe

2008 ◽  
Vol 57 (12) ◽  
pp. 7955
Author(s):  
Lai Xiao-Ming ◽  
Bian Bao-Min ◽  
Yang Ling ◽  
Yang Juan ◽  
Bian Niu ◽  
...  
Keyword(s):  
Perfect Gas ◽  
Self Similarity ◽  
Similarity Model

Quantifying uncertainties in multi-scale studies of fractured reservoir analogues: Implemented statistical analysis of scan line data from carbonate rocks

2010 ◽  
Vol 32 (9) ◽  
pp. 1271-1278 ◽  
Author(s):  
Vincenzo Guerriero ◽  
Alessandro Iannace ◽  
Stefano Mazzoli ◽  
Mariano Parente ◽  
Stefano Vitale ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Carbonate Rocks ◽  
Fractured Reservoir ◽  
Multi Scale ◽  
Scan Line

A Novel Network Traffic Anomaly Detection Based on Multi-Scale Fusion

2011 ◽  
Vol 48-49 ◽  
pp. 102-105
Author(s):  
Guo Zhen Cheng ◽  
Dong Nian Cheng ◽  
He Lei
Keyword(s):  
Anomaly Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Network Traffic ◽  
Self Similarity ◽  
Data Set ◽  
Multi Scale ◽  
Traffic Anomaly ◽  
Detection Evaluation ◽  
Better Than

Detecting network traffic anomaly is very important for network security. But it has high false alarm rate, low detect rate and that can’t perform real-time detection in the backbone very well due to its nonlinearity, nonstationarity and self-similarity. Therefore we propose a novel detection method—EMD-DS, and prove that it can reduce mean error rate of anomaly detection efficiently after EMD. On the KDD CUP 1999 intrusion detection evaluation data set, this detector detects 85.1% attacks at low false alarm rate which is better than some other systems.

Probing multi-scale self-similarity of tissue structures using light scattering spectroscopy: prospects in pre-cancer detection

2013 ◽  
Author(s):  
Subhasri Chatterjee ◽  
Nandan K. Das ◽  
Satish Kumar ◽  
Sonali Mohapatra ◽  
Asima Pradhan ◽  
...  
Keyword(s):  
Light Scattering ◽  
Cancer Detection ◽  
Self Similarity ◽  
Multi Scale ◽  
Light Scattering Spectroscopy ◽  
Tissue Structures

Effective Subgrid Modeling From the ILES Simulation of Compressible Turbulence

2007 ◽  
Vol 129 (12) ◽  
pp. 1493-1496 ◽  
Author(s):  
William J. Rider
Keyword(s):  
Incompressible Flows ◽  
Stokes Equations ◽  
Standard Form ◽  
Large Eddy Simulations ◽  
Compressible Turbulence ◽  
Navier Stokes ◽  
Subgrid Scale ◽  
Self Similarity ◽  
Large Eddy ◽  
Similarity Model

Implicit large eddy simulation (ILES) has provided many computer simulations with an efficient and effective model for turbulence. The capacity for ILES has been shown to arise from a broad class of numerical methods with specific properties producing nonoscillatory solutions using limiters that provide these methods with nonlinear stability. The use of modified equation has allowed us to understand the mechanisms behind the efficacy of ILES as a model. Much of the understanding of the ILES modeling has proceeded in the realm of incompressible flows. Here, we extend this analysis to compressible flows. While the general conclusions are consistent with our previous findings, the compressible case has several important distinctions. Like the incompressible analysis, the ILES of compressible flow is dominated by an effective self-similarity model (Bardina, J., Ferziger, J. H., and Reynolds, W. C., 1980, “Improved Subgrid Scale Models for Large Eddy Simulations,” AIAA Paper No. 80–1357; Borue, V., and Orszag, S. A., 1998, “Local Energy Flux and Subgrid-Scale Statistics in Three Dimensional Turbulence,” J. Fluid Mech., 366, pp. 1–31; Meneveau, C., and Katz, J., 2000, “Scale-Invariance and Turbulence Models for Large-Eddy Simulations,” Annu. Rev. Fluid. Mech., 32, pp. 1–32). Here, we focus on one of these issues, the form of the effective subgrid model for the conservation of mass equations. In the mass equation, the leading order model is a self-similarity model acting on the joint gradients of density and velocity. The dissipative ILES model results from the limiter and upwind differencing resulting in effects proportional to the acoustic modes in the flow as well as the convective effects. We examine the model in several limits including the incompressible limit. This equation differs from the standard form found in the classical Navier–Stokes equations, but generally follows the form suggested by Brenner (2005, “Navier-Stokes Revisited,” Physica A, 349(1–2), pp. 60–133) in a modification of Navier–Stokes necessary to successfully reproduce some experimentally measured phenomena. The implications of these developments are discussed in relation to the usual turbulence modeling approaches.

scholarly journals AN ANALYSIS OF CROSS-SHORE PROFILE EVOLUTION OF A SAND AND A COMPOSITE SAND-GRAVEL BEACHES

2012 ◽  
Vol 1 (33) ◽  
pp. 18
Author(s):  
Harshinie Karunarathna ◽  
Jose Horrillo-Caraballo ◽  
Roshanka Ranasinghe ◽  
Andrew Short ◽  
Dominic Reeve
Keyword(s):  
Statistical Analysis ◽  
Beach Erosion ◽  
Eof Analysis ◽  
Equilibrium Concept ◽  
Event Scale ◽  
Multi Scale ◽  
Differential Behavior ◽  
Equilibrium Profile ◽  
Annual Scale ◽  
Morphodynamic Evolution

In this paper, cross-shore morphodynamic evolution of a sand and sand-gravel composite beach, are compared and contrasted used historic surveys of beach profiles. The differential behavior of cross-shore morphodynamics at a range of time scales covering event-scale dynamics up to intra-annual scale variability are investigated and discussed. The application of equilibrium concept to both beach types is explored through Dean’s equilibrium profile and Vellinga’s beach erosion profile. Variability of cross-shore profile dynamics are quantified and discussed through bulk statistical analysis. Multi-scale morphodynamic trends are determined using Empirical Orthogonal Eigenfunction (EOF) analysis. The above analysis enables to recognise failure mechanism of each beach type during a storm.

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