1,107 research outputs found

    Well-posedness of the Viscous Boussinesq System in Besov Spaces of Negative Order Near Index s=1s=-1

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    This paper is concerned with well-posedness of the Boussinesq system. We prove that the nn (n2n\ge2) dimensional Boussinesq system is well-psoed for small initial data (u0,θ0)(\vec{u}_0,\theta_0) (u0=0\nabla\cdot\vec{u}_0=0) either in (B,11B,1,1)×Bp,r1({B}^{-1}_{\infty,1}\cap{B^{-1,1}_{\infty,\infty}})\times{B}^{-1}_{p,r} or in B,1,1×Bp,1,ϵ{B^{-1,1}_{\infty,\infty}}\times{B}^{-1,\epsilon}_{p,\infty} if r[1,]r\in[1,\infty], ϵ>0\epsilon>0 and p(n2,)p\in(\frac{n}{2},\infty), where Bp,qs,ϵB^{s,\epsilon}_{p,q} (sRs\in\mathbb{R}, 1p,q1\leq p,q\leq\infty, ϵ>0\epsilon>0) is the logarithmically modified Besov space to the standard Besov space Bp,qsB^{s}_{p,q}. We also prove that this system is well-posed for small initial data in (B,11B,1,1)×(Bn2,11Bn2,1,1)({B}^{-1}_{\infty,1}\cap{B^{-1,1}_{\infty,\infty}})\times({B}^{-1}_{\frac{n}{2},1}\cap{B^{-1,1}_{\frac{n}{2},\infty}}).Comment: 18 page

    Dynamic Transitions for Quasilinear Systems and Cahn-Hilliard equation with Onsager mobility

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    The main objectives of this article are two-fold. First, we study the effect of the nonlinear Onsager mobility on the phase transition and on the well-posedness of the Cahn-Hilliard equation modeling a binary system. It is shown in particular that the dynamic transition is essentially independent of the nonlinearity of the Onsager mobility. However, the nonlinearity of the mobility does cause substantial technical difficulty for the well-posedness and for carrying out the dynamic transition analysis. For this reason, as a second objective, we introduce a systematic approach to deal with phase transition problems modeled by quasilinear partial differential equation, following the ideas of the dynamic transition theory developed recently by Ma and Wang

    The Department of Commerce Under Herbert Hoover 1921-1928

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    Global Continua of Positive Equilibria for some Quasilinear Parabolic Equation with a Nonlocal Initial Condition

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    This paper is concerned with a quaslinear parabolic equation including a nonlinear nonlocal initial condition. The problem arises as equilibrium equation in population dynamics with nonlinear diffusion. We make use of global bifurcation theory to prove existence of an unbounded continuum of positive solutions

    Regularity properties of distributions through sequences of functions

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    We give necessary and sufficient criteria for a distribution to be smooth or uniformly H\"{o}lder continuous in terms of approximation sequences by smooth functions; in particular, in terms of those arising as regularizations (Tϕn)(T\ast\phi_{n}).Comment: 10 page

    DOT: Dynamic Object Tracking for Visual SLAM

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    In this paper we present DOT (Dynamic Object Tracking), a front-end that added to existing SLAM systems can significantly improve their robustness and accuracy in highly dynamic environments. DOT combines instance segmentation and multi-view geometry to generate masks for dynamic objects in order to allow SLAM systems based on rigid scene models to avoid such image areas in their optimizations. To determine which objects are actually moving, DOT segments first instances of potentially dynamic objects and then, with the estimated camera motion, tracks such objects by minimizing the photometric reprojection error. This short-term tracking improves the accuracy of the segmentation with respect to other approaches. In the end, only actually dynamic masks are generated. We have evaluated DOT with ORB-SLAM 2 in three public datasets. Our results show that our approach improves significantly the accuracy and robustness of ORB-SLAM 2, especially in highly dynamic scenes

    Geodesic distance for right invariant Sobolev metrics of fractional order on the diffeomorphism group

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    We study Sobolev-type metrics of fractional order s0s\geq0 on the group \Diff_c(M) of compactly supported diffeomorphisms of a manifold MM. We show that for the important special case M=S1M=S^1 the geodesic distance on \Diff_c(S^1) vanishes if and only if s12s\leq\frac12. For other manifolds we obtain a partial characterization: the geodesic distance on \Diff_c(M) vanishes for M=R×N,s<12M=\R\times N, s<\frac12 and for M=S1×N,s12M=S^1\times N, s\leq\frac12, with NN being a compact Riemannian manifold. On the other hand the geodesic distance on \Diff_c(M) is positive for dim(M)=1,s>12\dim(M)=1, s>\frac12 and dim(M)2,s1\dim(M)\geq2, s\geq1. For M=RnM=\R^n we discuss the geodesic equations for these metrics. For n=1n=1 we obtain some well known PDEs of hydrodynamics: Burgers' equation for s=0s=0, the modified Constantin-Lax-Majda equation for s=12s=\frac 12 and the Camassa-Holm equation for s=1s=1.Comment: 16 pages. Final versio

    On the high-low method for NLS on the hyperbolic space

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    In this paper, we first prove that the cubic, defocusing nonlinear Schr\"odinger equation on the two dimensional hyperbolic space with radial initial data in Hs(H2)H^s(\mathbb{H}^2) is globally well-posed and scatters when s>34s > \frac{3}{4}. Then we extend the result to nonlineraities of order p>3p>3. The result is proved by extending the high-low method of Bourgain in the hyperbolic setting and by using a Morawetz type estimate proved by the first author and Ionescu.Comment: The result is extended to general nonlineraitie

    Medial Features for Superpixel Segmentation

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    Image segmentation plays an important role in computer vision and human scene perception. Image oversegmentation is a common technique to overcome the problem of managing the high number of pixels and the reasoning among them. Specifically, a local and coherent cluster that contains a statistically homogeneous region is denoted as a superpixel. In this paper we propose a novel algorithm that segments an image into superpixels employing a new kind of shape centered feature which serve as a seed points for image segmentation, based on Gradient Vector Flow fields (GVF) [14]. The features are located at image locations with salient symmetry. We compare our algorithm to state-of-the-art superpixel algorithms and demonstrate a performance increase on the standard Berkeley Segmentation Dataset
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