23,922 research outputs found

    GMM-Based Hidden Markov Random Field for Color Image and 3D Volume Segmentation

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    In this project, we first study the Gaussian-based hidden Markov random field (HMRF) model and its expectation-maximization (EM) algorithm. Then we generalize it to Gaussian mixture model-based hidden Markov random field. The algorithm is implemented in MATLAB. We also apply this algorithm to color image segmentation problems and 3D volume segmentation problems

    HMRF-EM-image: Implementation of the Hidden Markov Random Field Model and its Expectation-Maximization Algorithm

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    In this project, we study the hidden Markov random field (HMRF) model and its expectation-maximization (EM) algorithm. We implement a MATLAB toolbox named HMRF-EM-image for 2D image segmentation using the HMRF-EM framework. This toolbox also implements edge-prior-preserving image segmentation, and can be easily reconfigured for other problems, such as 3D image segmentation.Comment: This work originally appears as the final project of Prof. Birsen Yazici's course Detection and Estimation Theory at RP

    Non-flow, and what flow to subtract in jet-correlation

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    We derive analytical forms for non-flow contributions from cluster correlation to two-particle elliptic flow (v2{2}) measure. We also derive an analytical form for jet-correlation flow-background with the same cluster approach. We argue that the elliptic flow v2 parameter to be used in jet-correlation background is that from two-particle method excluding non-flow correlations unrelated to the reaction plane, but including cross-terms between cluster correlation and cluster flow. We verify our result with Monte Carlo simulations. We discuss how one may obtain the v2 parameter for jet-correlation background experimentally.Comment: 11 pages 1 table 1 figure. Proceedings of 4th international workshop on High-pT physics at LHC-09, 2009, Prague, Czech Republi

    Dynamic bifurcation and instability of Dean problem

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    The main objective of this paper is to address the instability and dynamical bifurcation of the Dean problem. A nonlinear theory is obtained for the Dean problem, leading in particular to rigorous justifications of the linear theory used by physicists, and the vortex structure. The main technical tools are the dynamic bifurcation theory [15] developed recently by Ma and Wang.Comment: 16 pages,1figur

    Multiply Warped Products with a Quarter-symmetric Connection

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    In this paper, we study the Einstein warped products and multiply warped products with a quarter-symmetric connection. We also study warped products and multiply warped products with a quarter-symmetric connection with constant scalar curvature. Then apply our results to generalized Robertson-Walker spacetimes with a quarter-symmetric connection and generalized Kasner space-times with a quarter-symmetric connection.Comment: 41 pages. arXiv admin note: text overlap with arXiv:1207.509

    Influence of inelastic relaxation time on intrinsic spin Hall effects in a disordered two-dimensional electron gas

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    The influence of inelastic relaxation time on the intrinsic spin Hall effects in a disordered two-dimensional electron gas with Rashba interaction is studied, which clarifies the controversy of impurity effects in the system. We reveal that, due to the existence of inelastic scattering, the spin Hall conductivity does not vanish when the impurity concentration diminishes to zero no matter it is non-magnetically or magnetically disordered. The spin accumulation is evaluated by using the obtained spin Hall conductivity, and an alternate route is suggested to verify the intrinsic spin Hall effect by measuring the spin accumulation at different ratios.Comment: Revtex 6 pages, 1 figure, extended with more detail

    Probing the excited-state quantum phase transition through statistics of Loschmidt echo and quantum work

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    By analyzing the probability distributions of the Loschmidt echo (LE) and quantum work, we examine the nonequilibrium effects of a quantum many-body system, which exhibits an excited-state quantum phase transition (ESQPT). We find that depending on the value of the controlling parameter the distribution of the LE displays different patterns. At the critical point of the ESQPT, both the averaged LE and the averaged work show a cusplike shape. Furthermore, by employing the finite-size scaling analysis of the averaged work, we obtain the critical exponent of the ESQPT. Finally, we show that at the critical point of ESQPT the eigenstate is a highly localized state, further highlighting the influence of the ESQPT on the properties of the many-body system.Comment: 10 pages, 13 figures; accepted for publication in Physical Review

    Half-arc-transitive graphs of prime-cube order of small valencies

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    A graph is called {\em half-arc-transitive} if its full automorphism group acts transitively on vertices and edges, but not on arcs. It is well known that for any prime pp there is no tetravalent half-arc-transitive graph of order pp or p2p^2. Xu~[Half-transitive graphs of prime-cube order, J. Algebraic Combin. 1 (1992) 275-282] classified half-arc-transitive graphs of order p3p^3 and valency 44. In this paper we classify half-arc-transitive graphs of order p3p^3 and valency 66 or 88. In particular, the first known infinite family of half-arc-transitive Cayley graphs on non-metacyclic pp-groups is constructed.Comment: 13 page

    Feature Learning by Multidimensional Scaling and its Applications in Object Recognition

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    We present the MDS feature learning framework, in which multidimensional scaling (MDS) is applied on high-level pairwise image distances to learn fixed-length vector representations of images. The aspects of the images that are captured by the learned features, which we call MDS features, completely depend on what kind of image distance measurement is employed. With properly selected semantics-sensitive image distances, the MDS features provide rich semantic information about the images that is not captured by other feature extraction techniques. In our work, we introduce the iterated Levenberg-Marquardt algorithm for solving MDS, and study the MDS feature learning with IMage Euclidean Distance (IMED) and Spatial Pyramid Matching (SPM) distance. We present experiments on both synthetic data and real images --- the publicly accessible UIUC car image dataset. The MDS features based on SPM distance achieve exceptional performance for the car recognition task.Comment: To appear in SIBGRAPI 201

    Bipartite bi-Cayley graphs over metacyclic groups of odd prime-power order

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    A graph Γ\Gamma is a bi-Cayley graph over a group GG if GG is a semiregular group of automorphisms of Γ\Gamma having two orbits. Let GG be a non-abelian metacyclic pp-group for an odd prime pp, and let Γ\Gamma be a connected bipartite bi-Cayley graph over the group GG. In this paper, we prove that GG is normal in the full automorphism group Aut(Γ){\rm Aut}(\Gamma) of Γ\Gamma when GG is a Sylow pp-subgroup of Aut(Γ){\rm Aut}(\Gamma). As an application, we classify half-arc-transitive bipartite bi-Cayley graphs over the group GG of valency less than 2p2p. Furthermore, it is shown that there are no semisymmetric and no arc-transitive bipartite bi-Cayley graphs over the group GG of valency less than pp.Comment: 20 pages, 1 figur
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