The Experts below are selected from a list of 78 Experts worldwide ranked by ideXlab platform
Santiago Ospina - One of the best experts on this subject based on the ideXlab platform.
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Hamiltonicity in Semi-Regular Tessellation Dual Graphs.
arXiv: Computational Complexity, 2019Co-Authors: Divya Gopinath, Rohan Kodialam, Jayson Lynch, Santiago OspinaAbstract:This paper shows NP-completeness for finding Hamiltonian cycles in induced subgraphs of the dual graphs of semi-Regular tessilations. It also shows NP-hardness for a new, wide class of graphs called augmented square grids. This work follows up on prior studies of the complexity of finding Hamiltonian cycles in Regular and semi-Regular grid graphs.
Alfredo Navarra - One of the best experts on this subject based on the ideXlab platform.
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arbitrary pattern formation on infinite Regular Tessellation graphs
International Conference of Distributed Computing and Networking, 2021Co-Authors: Serafino Cicerone, Alessia Di Fonso, Gabriele Di Stefano, Alfredo NavarraAbstract:Given a set R of robots, each one located at a different vertex of an infinite Regular Tessellation graph, we aim to explore the Arbitrary Pattern Formation (APF) problem. Given a multiset F of grid vertices such that |R| = |F|, APF asks for a distributed algorithm that moves robots so as to reach a configuration similar to F. Similarity means that robots must be disposed as F regardless of translations, rotations, reflections. So far, as possible discretization of the Euclidean plane only the standard square grid has been considered in the context of the classical Look-Compute-Move model. However, it is natural to consider the other Regular Tessellation graphs, that are triangular and hexagonal grids. For any Regular Tessellation graph, we provide a resolution algorithm for APF when the initial configuration is asymmetric.
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arbitrary pattern formation on infinite Regular Tessellation graphs
arXiv: Distributed Parallel and Cluster Computing, 2020Co-Authors: Serafino Cicerone, Alessia Di Fonso, Gabriele Di Stefano, Alfredo NavarraAbstract:Given a set R of robots, each one located at different vertices of an infinite Regular Tessellation graph, we aim to explore the Arbitrary Pattern Formation (APF) problem. Given a multiset F of grid vertices such that |R|=|F|, APF asks for a distributed algorithm that moves robots so as to reach a configuration similar to F. Similarity means that robots must be disposed as F regardless of translations, rotations, reflections. So far, as possible graph discretizing the Euclidean plane only the standard square grid has been considered in the context of the classical Look-Compute-Move model. However, it is natural to consider also the other Regular Tessellation graphs, that are triangular and hexagonal grids. We provide a resolution algorithm for APF when the initial configuration is asymmetric and the considered topology is any Regular Tessellation graph.
Matthias Goerner - One of the best experts on this subject based on the ideXlab platform.
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Regular Tessellation links
2014Co-Authors: Matthias GoernerAbstract:By Regular Tessellation, we mean any hyperbolic 3-manifold tessellated by ideal Platonic solids such that the symmetry group acts transitively on oriented flags. A Regular Tessellation has an invariant we call the cusp modulus. For small cusp modulus, we classify all Regular Tessellations. For large cusp modulus, we prove that a Regular Tessellations has to be infinite volume if its fundamental group is generated by peripheral curves only. This shows that there are at least 19 and at most 21 link complements that are Regular Tessellations (computer experiments suggest that at least one of the two remaining cases likely fails to be a link complement, but so far we have no proof). In particular, we complete the classification of all principal congruence link complements given in Baker and Reid for the cases of discriminant D=-3 and D=-4. We only describe the manifolds arising as complements of links here with a future publication "Regular Tessellation Links" giving explicit pictures of these links.
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Regular Tessellation link complements
arXiv: Geometric Topology, 2014Co-Authors: Matthias GoernerAbstract:By Regular Tessellation, we mean any hyperbolic 3-manifold tessellated by ideal Platonic solids such that the symmetry group acts transitively on oriented flags. A Regular Tessellation has an invariant we call the cusp modulus. For small cusp modulus, we classify all Regular Tessellations. For large cusp modulus, we prove that a Regular Tessellations has to be infinite volume if its fundamental group is generated by peripheral curves only. This shows that there are at least 19 and at most 21 link complements that are Regular Tessellations (computer experiments suggest that at least one of the two remaining cases likely fails to be a link complement, but so far we have no proof). In particular, we complete the classification of all principal congruence link complements given in Baker and Reid for the cases of discriminant D=-3 and D=-4. We only describe the manifolds arising as complements of links here with a future publication "Regular Tessellation Links" giving explicit pictures of these links.
Quanhua Zhao - One of the best experts on this subject based on the ideXlab platform.
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coupling Regular Tessellation with rjmcmc algorithm to segment sar image with unknown number of classes
ISPRS - International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, 2016Co-Authors: Y Wang, Quanhua ZhaoAbstract:Abstract. This paper presents a Synthetic Aperture Radar (SAR) image segmentation approach with unknown number of classes, which is based on Regular Tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC') algorithm. First of all, an image domain is portioned into a set of blocks by Regular Tessellation. The image is modeled on the assumption that intensities of its pixels in each homogeneous region satisfy an identical and independent Gamma distribution. By Bayesian paradigm, the posterior distribution is obtained to build the region-based image segmentation model. Then, a RJMCMC algorithm is designed to simulate from the segmentation model to determine the number of homogeneous regions and segment the image. In order to further improve the segmentation accuracy, a refined operation is performed. To illustrate the feasibility and effectiveness of the proposed approach, two real SAR image is tested.
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segmentation of high resolution sar image with unknown number of classes based on Regular Tessellation and rjmcmc algorithm
Journal of remote sensing, 2015Co-Authors: Y Wang, Quanhua ZhaoAbstract:This article presents a statistics- and region-based approach to segmentation of synthetic aperture radar (SAR) images. The proposed approach can automatically determine the number of classes and segment the image simultaneously. First of all, an image domain is partitioned into a set of blocks by Regular Tessellation and the image is modelled on the assumption that intensities of its pixels in each homogeneous region satisfy an identical and independent gamma distribution. The Bayesian paradigm is followed to build an image segmentation model. Then, a Reversible Jump Markov Chain Monte Carlo scheme is designed to simulate the segmentation model, which determines the number of classes and segments the image roughly. Furthermore, in order to improve the accuracy of the segmentation results, refined operation is performed. The results obtained from both real and simulated SAR images show that the proposed approach works well and efficient.
Divya Gopinath - One of the best experts on this subject based on the ideXlab platform.
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Hamiltonicity in Semi-Regular Tessellation Dual Graphs.
arXiv: Computational Complexity, 2019Co-Authors: Divya Gopinath, Rohan Kodialam, Jayson Lynch, Santiago OspinaAbstract:This paper shows NP-completeness for finding Hamiltonian cycles in induced subgraphs of the dual graphs of semi-Regular tessilations. It also shows NP-hardness for a new, wide class of graphs called augmented square grids. This work follows up on prior studies of the complexity of finding Hamiltonian cycles in Regular and semi-Regular grid graphs.