The Experts below are selected from a list of 114 Experts worldwide ranked by ideXlab platform
Ma Shao-xian - One of the best experts on this subject based on the ideXlab platform.
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Adjacent strong Edge coloring of P_m∨F_n
Journal of Lanzhou University, 2020Co-Authors: Ma Shao-xianAbstract:A proper Edge coloring is called adjacent strong Edge coloring if colored sets from every two adjacent vertices' Incident Edge are different.The minimum number of colors required for an adjacent strong Edge coloring,a simple graph G is denoted byχ′_(as)(G).In this paper,we have given the adjacent strong Edge chromatic number of P_m∨F_n.
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On Adjacent Vertex Distinguishing Total Coloring of P_m∨S_n
Journal of East China Jiaotong University, 2020Co-Authors: Ma Shao-xianAbstract:A total-coloring is called adjacent vertex-distinguishing if every two adjacent vertices are Incident to different sets of colored vertex and Incident Edge with vertex.The minimum number of colors required for an adjacent vertex-distinguishing proper total-coloring,a simple graph G is denoted by χ_(at)(G).In this paper,we obtain the adjacent vertex distinguishing total chromatic number of P_m∨S_n.
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On Adjacent Strong Vertex-Distinguishing Total Coloring of P_m×C_n
Journal of Guizhou University, 2020Co-Authors: Ma Shao-xianAbstract:A total-coloring of a graph is called adjacent strong vertex-distinguishing if any two adjacent vertices are Incident to different sets of colored vertex and Incident Edge with vertex.The minimum number of colors which were required for a adjacent vertex-distinguishing proper total coloring is called the adjacent strong vertex-distinguishing total chromatic number.The adjacent strong vertex distinguishing total chromatic number of Pm×Cn were given in this paper.
X. Cavin - One of the best experts on this subject based on the ideXlab platform.
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IEEE Visualization - Circular Incident Edge lists: a data structure for rendering complex unstructured grids
Proceedings Visualization 2001. VIS '01., 2001Co-Authors: B. Levy, G. Caumon, S. Conreaux, X. CavinAbstract:We present the circular Incident Edge lists (CIEL), a new data structure and a high-performance algorithm for generating a series of iso-surfaces in a highly unstructured grid. Slicing-based volume rendering is also considered. The CIEL data structure represents all the combinatorial information of the grid, making it possible to optimize the classical propagation from local minima paradigm. The usual geometric structures are replaced by a more efficient combinatorial structure. An active Edges list is maintained, and iteratively propagated from an iso-surface to the next one in a very efficient way. The intersected cells Incident to each active Edge are retrieved, and the intersection polygons are generated by circulating around their facets. This latter feature enables arbitrary irregular cells to be treated, such as those encountered in certain computational fluid dynamics (CFD) simulations. Since the CIEL data structure solely depends on the connections between the cells, it is possible to take into account dynamic changes in the geometry of the mesh and in property values, which only requires the sorted extrema list to be updated. Experiments have shown that our approach is significantly faster than classical methods. The major drawback of our method is its memory consumption, higher than most classical methods. However, experimental results show that it stays within a practical range.
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Circular Incident Edge lists: a data structure for rendering complex unstructured grids
Proceedings Visualization 2001. VIS '01., 2001Co-Authors: B. Levy, G. Caumon, S. Conreaux, X. CavinAbstract:We present the circular Incident Edge lists (CIEL), a new data structure and a high-performance algorithm for generating a series of iso-surfaces in a highly unstructured grid. Slicing-based volume rendering is also considered. The CIEL data structure represents all the combinatorial information of the grid, making it possible to optimize the classical propagation from local minima paradigm. The usual geometric structures are replaced by a more efficient combinatorial structure. An active Edges list is maintained, and iteratively propagated from an iso-surface to the next one in a very efficient way. The intersected cells Incident to each active Edge are retrieved, and the intersection polygons are generated by circulating around their facets. This latter feature enables arbitrary irregular cells to be treated, such as those encountered in certain computational fluid dynamics (CFD) simulations. Since the CIEL data structure solely depends on the connections between the cells, it is possible to take into account dynamic changes in the geometry of the mesh and in property values, which only requires the sorted extrema list to be updated. Experiments have shown that our approach is significantly faster than classical methods. The major drawback of our method is its memory consumption, higher than most classical methods. However, experimental results show that it stays within a practical range.
Ma Gang - One of the best experts on this subject based on the ideXlab platform.
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The Adjacent Strong Edge Coloring on Some Double Graph
Journal of Gansu Lianhe University, 2020Co-Authors: Ma GangAbstract:A proper Edge coloring is called adjacent strong Edge coloring if colored sets from every two adjacent vertices Incident Edge are different,the minimum number of colors is called adjacent strong Edge chromatic number.In this paper,the adjacent strong Edge chromatic number of double graphs of star,fan,and wheel were obtained.
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On Adjacent Vertex Distinguishing Total Coloring of C_m∨F_n
Journal of Northwest Minorities University for Nationalities, 2020Co-Authors: Ma GangAbstract:A total-coloring is called adjacent vertex-distinguishing if every two adjacent vertices are Incident to different sets of colored vertex and Incident Edge with vertex. The minimum number of colors required for an adjacent vertex-distinguishing proper total-coloring, a simple graph G is denoted by ., The adjacent vertex distinguishing total chromatic number of have been given in this paper.
Sanguthevar Rajasekaran - One of the best experts on this subject based on the ideXlab platform.
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Randomized Selection on the Hypercube
Journal of Parallel and Distributed Computing, 1996Co-Authors: Sanguthevar RajasekaranAbstract:In this paper, we present randomized algorithms for selection on the hypercube. We identify two variants of the hypercube, namely, thesequential modeland theparallel model. In the sequential model, any node at any time can handle only communication along a single Incident Edge, whereas in the parallel model a node can communicate along all its Incident Edges at the same time. We specify three variations of the parallel model and present optimal randomized algorithms on all these three versions of parallel model. In particular, we show that selection on an input of sizencan be performed on ap-node hypercube in timeO((n/p) + logp) with high probability, on any of the three versions of the parallel model. This result is important in view of a lower bound that implies that selection needs ?((n/p)log logp+ logp) time on ap-node sequential hypercube. We modify our selection algorithm to run on the sequential hypercube in which case it runs in an expected time nearly matching this lower bound. For the special case whenn=p, our selection algorithm runs in an optimalO(logn) time on the sequential hypercube. Our algorithms are very simple and are most likely to perform well in practice.
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Randomized selection on the hypercube
Journal of Parallel and Distributed Computing, 1996Co-Authors: Sanguthevar RajasekaranAbstract:In this paper, we present randomized algorithms for selection on the hypercube. We identify two variants of the hypercube, namely, the sequential model and the parallel model. In the sequential model, any node at any time can handle only communication along a single Incident Edge, whereas in the parallel model a node can communicate along all its Incident Edges at the same time. We specify three variations of the parallel model and present optimal randomized algorithms on all these three versions of parallel model. In particular, we show that selection on an input of size n can be performed on a p-node hypercube in time O((nlp) + log p) with high probability, on any of the three versions of the parallel model. This result is important in view of a lower bound that implies that selection needs Ω((n/p)log log p + log p) time on a p-node sequential hypercube. We modify our selection algorithm to run on the sequential hypercube in which case it runs in an expected time nearly matching this lower bound. For the special case when n = p, our selection algorithm runs in an optimal O(log n) time on the sequential hypercube. Our algorithms are very simple and are most likely to perform well in practice. © 1996 Academic Press, Inc.
Eli Packer - One of the best experts on this subject based on the ideXlab platform.
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Iterated snap rounding with bounded drift
Computational Geometry: Theory and Applications, 2008Co-Authors: Eli PackerAbstract:Snap Rounding and its variant, Iterated Snap Rounding, are methods for converting arbitrary-precision arrangements of segments into a fixed-precision representation (we call them SR and ISR for short). Both methods approximate each original segment by a polygonal chain, and both may lead, for certain inputs, to rounded arrangements with undesirable properties: in SR the distance between a vertex and a non-Incident Edge of the rounded arrangement can be extremely small, inducing potential degeneracies. In ISR, a vertex and a non-Incident Edge are well separated, but the approximating chain may drift far away from the original segment it approximates. We propose a new variant, Iterated Snap Rounding with Bounded Drift, which overcomes these two shortcomings of the earlier methods. The new solution augments ISR with simple and efficient procedures that guarantee the quality of the geometric approximation of the original segments, while still maintaining the property that a vertex and a non-Incident Edge in the rounded arrangement are well separated. We investigate the properties of the new method and compare it with the earlier variants. We have implemented the new scheme on top of CGAL, the Computational Geometry Algorithms Library, and report on experimental results.
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Symposium on Computational Geometry - Iterated snap rounding with bounded drift
Proceedings of the twenty-second annual symposium on Computational geometry - SCG '06, 2006Co-Authors: Eli PackerAbstract:Snap Rounding and its variant, Iterated Snap Rounding, are methods for converting arbitrary-precision arrangements of segments into a fixed-precision representation (we call them SR and ISR for short). Both methods approximate each original segment by a polygonal chain, and both may lead, for certain inputs, to rounded arrangements with undesirable properties: in SR the distance between a vertex and a non-Incident Edge of the rounded arrangement can be extremely small, inducing potential degeneracies. In ISR, a vertex and a non-Incident Edge are well separated, but the approximating chain may drift far away from the original segment it approximates. We propose a new variant, Iterated Snap Rounding with Bounded Drift, which overcomes these two shortcomings of the earlier methods. The new solution augments ISR with simple and efficient procedures that guarantee the quality of the geometric approximation of the original segments, while still maintaining the property that a vertex and a non-Incident Edge in the rounded arrangement are well separated. We investigate the properties of the new method and compare it with the earlier variants. We have implemented the new scheme on top of CGAL, the Computational Geometry Algorithms Library, and report on experimental results.
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Iterated snap rounding
Computational Geometry: Theory and Applications, 2002Co-Authors: Dan Halperin, Eli PackerAbstract:Snap rounding is a well known method for converting arbitrary-precision arrangements of segments into a fixed-precision representation. We point out that in a snap-rounded arrangement, the distance between a vertex and a non-Incident Edge can be extremely small compared with the width of a pixel in the grid used for rounding. We propose and analyze an augmented procedure, iterated snap rounding, which rounds the arrangement such that each vertex is at least half-the-width-of-a-pixel away from any non-Incident Edge. Iterated snap rounding preserves the topology of the original arrangement in the same sense that the original scheme does. However, the guaranteed quality of the approximation degrades. Thus each scheme may be suitable in different situations. We describe an implementation of both schemes. In our implementation we substitute an intricate data structure for segment/pixel intersection that is used to obtain good worst-case resource bounds for iterated snap rounding by a simple and effective data structure which is a cluster of kd-trees. Finally, we present rounding examples obtained with the implementation.
