Results 21 to 30 of about 2,637,453 (146)

Front Propagation Through a Perforated Wall

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We consider a bistable reaction– diffusion equation ut=Δu+f(u)$u_t=\Delta u +f(u)$ on RN${\mathbb {R}}^N$ in the presence of an obstacle K$K$, which is a wall of infinite span with many holes. More precisely, K$K$ is a closed subset of RN${\mathbb {R}}^N$ with smooth boundary such that its projection onto the x1$x_1$‐axis is bounded and that ...
Henri Berestycki   +2 more
wiley   +1 more source

Hausdorff measures: area formula and coarea formula [PDF]

open access: yes, 2022
openQuesta tesi si propone di applicare le misure di Hausdorff per dimostrare due formule: la formula dell'area e la formula di coarea nel caso generale, ovvero per funzioni lipschtziane.
FAVARO, GABRIELE
core  

A Geometric Characterization of Steady Laminar Flow

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We study the steady states of the Euler equations on the periodic channel or annulus. We show that if these flows are laminar (layered by closed non‐contractible streamlines which foliate the domain), then they must be either parallel or circular flows.
Theodore D. Drivas, Marc Nualart
wiley   +1 more source

Bayesian Optimization of Grayscale Patterns for Layer‐Height Accuracy in Projection Multi‐Photon 3D Printing

open access: yesLaser &Photonics Reviews, EarlyView.
Bayesian optimization combined with in situ quantitative phase imaging enables autonomous correction of layer‐height deviations in projection multi‐photon lithography. By jointly tuning model parameters and grayscale exposure settings, the method achieves more uniform and accurate layers within 300 prints, offering a fast, data‐efficient route to ...
Jason E. Johnson, Xianfan Xu
wiley   +1 more source

On simultaneous local dimension functions of subsets of Rd [PDF]

open access: yes, 2015
Date of Acceptance: 04/05/2015For a subset E ⊑ Rd and x ∈ Rd, the local Hausdorff dimension function of E at x and the local packing dimension function of E at x are defined by (Formula presented.) where dimH and dimP denote the Hausdorff dimension and ...
Olsen, Lars Ole Ronnow
core   +1 more source

Survey on differential estimators for 3d point clouds

open access: yesComputer Graphics Forum, EarlyView.
Abstract Recent advancements in 3D scanning technologies, including LiDAR and photogrammetry, have enabled the precise digital replication of real‐world objects. These methods are widely used in fields such as GIS, robotics, and cultural heritage. However, the point clouds generated by such scans are often noisy and unstructured, posing challenges for ...
Léo Arnal–Anger   +4 more
wiley   +1 more source

Progressive Convex Hull Simplification

open access: yesComputer Graphics Forum, EarlyView.
Abstract Convex hulls are useful as tight bounding proxies for a variety of tasks including collision detection, ray intersection, and distance computation. Unfortunately, the complexity of polyhedral convex hulls grows linearly with their input. We consider the problem of conservatively simplifying a convex hull to a specified number of half‐spaces ...
Alec Jacobson
wiley   +1 more source

Resonances for graph directed Markov systems, and geometry of infinitely generated dynamical systems [PDF]

open access: yes, 2009
In the first part of this thesis we transfer a result of Guillopé et al. concerning the number of zeros of the Selberg zeta function for convex cocompact Schottky groups to the setting of certain types of graph directed Markov systems (GDMS ...
Hille, Martial R.
core   +1 more source

A practical algorithm for weighted k‐hulls

open access: yesComputer Graphics Forum, EarlyView.
Abstract The convex hull is a central concept in computational geometry, geometry processing, and generally for summarizing sampled data. Its descriptive power suffers significantly in the presence of noise. The k‐hull, also known as the k‐depth contour in statistics, is the intersection of all half‐spaces that contain all but k data points, i.e. it is
N. Look, H. Meyer, M. Alexa
wiley   +1 more source

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