Results 91 to 100 of about 26,406 (246)

Stagewise crop yield prediction with multisource functional indices

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Index insurance design involves integrating weather data, soil moisture, phenology information, and satellite imagery, which presents challenges in data fusion. This article addresses the modelling of multisource functional indices of varying lengths by constructing a stagewise ensemble of sequential models.
Jing Zou, Ostap Okhrin
wiley   +1 more source

Inertias of Laplacian matrices of weighted signed graphs

open access: yesSpecial Matrices, 2019
We study the sets of inertias achieved by Laplacian matrices of weighted signed graphs. First we characterize signed graphs with a unique Laplacian inertia.
Monfared K. Hassani   +3 more
doaj   +1 more source

Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver

open access: yesInternational Journal for Numerical Methods in Fluids, EarlyView.
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley   +1 more source

Laplacian‎ ‎Coefficients of a‎ ‎Forest in Terms of the Number of Closed Walks in the Forest and its Line Graph [PDF]

open access: yesMathematics Interdisciplinary Research
‎In this paper‎, ‎we deal with calculating the laplacian coefficients of a finite simple graph $G$ with the Laplacian polynomial $\psi(G,\lambda) = \sum_{k=0}^{n}(-1)^{n-k}c_k\lambda^k$‎.
Ali Ghalavand, Alireza Ashrafi
doaj   +1 more source

Fractional discrete Laplacian versus discretized fractional Laplacian

open access: yes, 2015
25 pages, 13 ...
Ciaurri, Ó.   +4 more
openaire   +2 more sources

Clinical Applications of Electrical Conductivity Imaging Using MRI

open access: yesJournal of Magnetic Resonance Imaging, EarlyView.
ABSTRACT Magnetic resonance imaging (MRI) has emerged as a noninvasive technique for probing the electrical properties of biological tissues: electrical conductivity and relative permittivity. This review focuses on the electrical conductivity and provides a comprehensive overview of applications across both low‐ and high‐frequency regimes.
Stefano Mandija   +14 more
wiley   +1 more source

Resolvent kernel for the Kohn Laplacian on Heisenberg groups

open access: yesElectronic Journal of Differential Equations, 2002
We present a formula that relates the Kohn Laplacian on Heisenberg groups and the magnetic Laplacian. Then we obtain the resolvent kernel for the Kohn Laplacian and find its spectral density.
Neur Eddine Askour, Zouhair Mouayn
doaj  

On the Eigenvalues and Energy of the Seidel and Seidel Laplacian Matrices of Graphs

open access: yesDiscrete Dynamics in Nature and Society
Let SΓ be a Seidel matrix of a graph Γ of order n and let DΓ=diagn−1−2d1,n−1−2d2,…,n−1−2dn be a diagonal matrix with di denoting the degree of a vertex vi in Γ. The Seidel Laplacian matrix of Γ is defined as SLΓ=DΓ−SΓ.
J. Askari   +2 more
doaj   +1 more source

A two‐stage model for precise identification and Gleason grading of clinically significant prostate cancer: a hybrid approach

open access: yesJournal of Medical Radiation Sciences, Volume 72, Issue 1, Page 93-105, March 2025.
This study developed a two‐stage model using radiomics‐based multiparametric MRI and clinical indicators to help identify and grade clinically significant prostate cancer. The model showed promising levels of diagnostic accuracy and predictive performance.
Yuyan Zou   +10 more
wiley   +1 more source

Estimate Laplacian Spectral Properties of Large-Scale Networks by Random Walks and Graph Transformation

open access: yesMathematics
For network graphs, numerous graph features are intimately linked to eigenvalues of the Laplacian matrix, such as connectivity and diameter. Thus, it is very important to solve eigenvalues of the Laplacian matrix for graphs.
Changlei Zhan, Xiangyu Li, Jie Chen
doaj   +1 more source

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