Search results for "pattern"
showing 10 items of 4203 documents
Testing the Outflow Process over a Triangular Labyrinth Weir
2017
In this paper, the dimensionless stage-discharge relation for a sharp-crested triangular labyrinth weir, determined in a previous study, is initially tested by some experimental runs carried out in a laboratory flume. According to this relationship, the flow magnification is affected by the length-magnification ratio and the head to one cycle width ratio. The measurements allowed to test the applicability of this dimensionless relation for different values of both the angle of the sidewall to the main flow direction and the weir height. Finally, the proposed dimensionless equation was also tested by using experimental measurements carried out for broad-crested triangular labyrinth weir.
Vegetation effects on cross-sectional flow in a large amplitude meandering bend
2017
ABSTRACTCross-stream circulation, which develops in meandering bends, exerts an important role in velocity redistribution. This paper investigates how the presence of vegetation could affect the evolution pattern of cross-stream flow along a high-curvature meandering bend. The analysis is conducted with the aid of data collected in a meandering laboratory flume over non-vegetated and vegetated beds. The experiments reveal that, once the vegetation is introduced, the flow pattern determined by the channel’s curvature is interrupted. In the presence of vegetation, the central-region circulation cell seems to be divided into thin circulation cells developing at the top of the vegetated layer a…
Analysis of soil surface component patterns affecting runoff generation. An example of methods applied to Mediterranean hillslopes in Alicante (Spain)
2008
Spatial patterns of soil surface components (vegetation, rock fragments, crusts, bedrock outcrops, etc.) are a key factor determining hydrological functioning of hillslopes. A methodological approach to analyse the patterns of soil surface components at a detailed scale is proposed in this paper. The methods proposed are applied to two contrasting semi-arid Mediterranean hillslopes, and the influence of soil surface component patterns on the runoff response of the slopes was analysed. A soil surface components map was derived from a high resolution photo-mosaic obtained in the field by means of a digital camera. Rainfall simulation experimental data were used to characterise the hydrologica…
Eckhaus instability of stationary patterns in hyperbolic reaction–diffusion models on large finite domains
2022
AbstractWe have theoretically investigated the phenomenon of Eckhaus instability of stationary patterns arising in hyperbolic reaction–diffusion models on large finite domains, in both supercritical and subcritical regime. Adopting multiple-scale weakly-nonlinear analysis, we have deduced the cubic and cubic–quintic real Ginzburg–Landau equations ruling the evolution of pattern amplitude close to criticality. Starting from these envelope equations, we have provided the explicit expressions of the most relevant dynamical features characterizing primary and secondary quantized branches of any order: stationary amplitude, existence and stability thresholds and linear growth rate. Particular em…
Hypergraph imaging: an overview
2002
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to seg…
Passive millimeter wave image classification with large scale Gaussian processes
2017
Passive Millimeter Wave Images (PMMWIs) are being increasingly used to identify and localize objects concealed under clothing. Taking into account the quality of these images and the unknown position, shape, and size of the hidden objects, large data sets are required to build successful classification/detection systems. Kernel methods, in particular Gaussian Processes (GPs), are sound, flexible, and popular techniques to address supervised learning problems. Unfortunately, their computational cost is known to be prohibitive for large scale applications. In this work, we present a novel approach to PMMWI classification based on the use of Gaussian Processes for large data sets. The proposed…
A Tsetlin Machine with Multigranular Clauses
2019
The recently introduced Tsetlin Machine (TM) has provided competitive pattern recognition accuracy in several benchmarks, however, requires a 3-dimensional hyperparameter search. In this paper, we introduce the Multigranular Tsetlin Machine (MTM). The MTM eliminates the specificity hyperparameter, used by the TM to control the granularity of the conjunctive clauses that it produces for recognizing patterns. Instead of using a fixed global specificity, we encode varying specificity as part of the clauses, rendering the clauses multigranular. This makes it easier to configure the TM because the dimensionality of the hyperparameter search space is reduced to only two dimensions. Indeed, it tur…
A Novel System for Multi-level Crohn’s Disease Classification and Grading Based on a Multiclass Support Vector Machine
2020
Crohn’s disease (CD) is a chronic inflammatory condition of the gastrointestinal tract that can highly alter patient’s quality of life. Diagnostic imaging, such as Enterography Magnetic Resonance Imaging (E-MRI), provides crucial information for CD activity assessment. Automatic learning methods play a fundamental role in the classification of CD and allow to avoid the long and expensive manual classification process by radiologists. This paper presents a novel classification method that uses a multiclass Support Vector Machine (SVM) based on a Radial Basis Function (RBF) kernel for the grading of CD inflammatory activity. To validate the system, we have used a dataset composed of 800 E-MRI…
Biophysical parameter estimation with adaptive Gaussian Processes
2009
We evaluate Gaussian Processes (GPs) for the estimation of biophysical parameters from acquired multispectral data. The standard GP formulation is used, and all hyperparameters (kernel parameters and noise variance) are optimized by maximizing the marginal likelihood. This gives rise to a fully-adaptive GP to data characteristics, both in terms of signal and noise properties. The good numerical results in the estimation of oceanic chlorophyll concentration and leaf membrane state confirm GPs as adequate, alternative non-parametric methods for biophysical parameter estimation. GPs are also analyzed by scrutinizing the predictive variance, the estimated noise variance, and the relevance of ea…
Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most rele…
2013
[EN] Green mold (Penicillium digitatum) and blue mold (Penicillium italicum) are important sources of postharvest decay affecting the commercialization of mandarins. These fungi infections produce enormous economic losses in mandarin production if early detection is not carried out. Nowadays, this detection is performed manually in dark chambers, where the fruit is illuminated by ultraviolet light to produce fluorescence, which is potentially dangerous for humans. This paper documents a new methodology based on hyperspectral imaging and advanced machine-learning techniques (artificial neural networks and classification and regression trees) for the segmentation and classification of images …