Search results for "Vector"
showing 10 items of 2660 documents
Flux of a Vector Field
2012
In this chapter we concentrate on aspects of vector calculus. A common physical application of this theory is the fluid flow problem of calculating the amount of fluid passing through a permeable surface. The abstract generalization of this leads us to the flux of a vector field through a regular 2-surface in \(\mathbb{R}^3\). More precisely, let the vector field F in \(\mathbb{R}^3\) represent the velocity vector field of a fluid. We immerse a permeable surface S in that fluid, and we are interested in the amount of fluid flow across the surface S per unit time. This is the flux integral of the vector field F across the surface S
Numerical modelling of asymmetric boudinage
2002
Abstract Asymmetric boudinage structures are commonly used as shear sense indicators but their development is incompletely understood. This paper describes the influence of initial shape and kinematic parameters on the evolution of boudin trains using a numerical approach based on the finite difference code FLAC. Boudin trains are simulated as a series of competent objects embedded in a soft matrix subjected to general monoclinic ductile flow. Deformation of boudin trains includes heterogeneous stretching, rotation of boudins and offset along the neck regions. The sense of relative boudin offset is mainly influenced by the initial orientation of the interboudin plane in the boudinaging laye…
Long-lived particles at the energy frontier: the MATHUSLA physics case
2019
We examine the theoretical motivations for long-lived particle (LLP) signals at the LHC in a comprehensive survey of Standard Model (SM) extensions. LLPs are a common prediction of a wide range of theories that address unsolved fundamental mysteries such as naturalness, dark matter, baryogenesis and neutrino masses, and represent a natural and generic possibility for physics beyond the SM (BSM). In most cases the LLP lifetime can be treated as a free parameter from the $\mu$m scale up to the Big Bang Nucleosynthesis limit of $\sim 10^7$m. Neutral LLPs with lifetimes above $\sim$ 100m are particularly difficult to probe, as the sensitivity of the LHC main detectors is limited by challenging …
Paratransgenic manipulation of a tsetse microRNA alters the physiological homeostasis of the fly’s midgut environment
2021
Tsetse flies are vectors of parasitic African trypanosomes, the etiological agents of human and animal African trypanosomoses. Current disease control methods include fly-repelling pesticides, fly trapping, and chemotherapeutic treatment of infected people and animals. Inhibiting tsetse’s ability to transmit trypanosomes by strengthening the fly’s natural barriers can serve as an alternative approach to reduce disease. The peritrophic matrix (PM) is a chitinous and proteinaceous barrier that lines the insect midgut and serves as a protective barrier that inhibits infection with pathogens. African trypanosomes must cross tsetse’s PM in order to establish an infection in the fly, and PM struc…
Superconvergence phenomenon in the finite element method arising from averaging gradients
1984
We study a superconvergence phenomenon which can be obtained when solving a 2nd order elliptic problem by the usual linear elements. The averaged gradient is a piecewise linear continuous vector field, the value of which at any nodal point is an average of gradients of linear elements on triangles incident with this nodal point. The convergence rate of the averaged gradient to an exact gradient in theL 2-norm can locally be higher even by one than that of the original piecewise constant discrete gradient.
Post-processing of Pixel and Object-Based Land Cover Classifications of Very High Spatial Resolution Images
2020
The state of the art is plenty of classification methods. Pixel-based methods include the most traditional ones. Although these achieved high accuracy when classifying remote sensing images, some limits emerged with the advent of very high-resolution images that enhanced the spectral heterogeneity within a class. Therefore, in the last decade, new classification methods capable of overcoming these limits have undergone considerable development. Within this research, we compared the performances of an Object-based and a Pixel-Based classification method, the Random Forests (RF) and the Object-Based Image Analysis (OBIA), respectively. Their ability to quantify the extension and the perimeter…
A support vector domain method for change detection in multitemporal images
2010
This paper formulates the problem of distinguishing changed from unchanged pixels in multitemporal remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere-shaped decision boundary with minimal volume that embraces changed pixels is approached in the context of the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. Unlike the standard SVDD, the proposed formulation of the SVDD uses both target and outlier samples for defi…
A Clustering Approach to texture Classification
1988
In the paper a clustering technique to segment an image in to “homogeneous” regions is studied. The homogeneity of each region is evaluated by means of a “proximity function” computed between the pixels. The main result of such approach is that no-histogramming is required in order to perform segmentation. Possibilistic and probabilistic approaches are, also, combined to evaluate the significativity of the computed regions.
Shape Description for Content-Based Image Retrieval
2000
The present work is focused on a global image characterization based on a description of the 2D displacements of the different shapes present in the image, which can be employed for CBIR applications.To this aim, a recognition system has been developed, that detects automatically image ROIs containing single objects, and classifies them as belonging to a particular class of shapes.In our approach we make use of the eigenvalues of the covariance matrix computed from the pixel rows of a single ROI. These quantities are arranged in a vector form, and are classified using Support Vector Machines (SVMs). The selected feature allows us to recognize shapes in a robust fashion, despite rotations or…
Cluster kernels for semisupervised classification of VHR urban images
2009
In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and wor…