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25
Generating Outerplanar Graphs
"... supported by the DFG (GRK 588/1) Abstract. We show how to generate labeled and unlabeled outerplanar graphs with n vertices uniformly at random in polynomial time in n. To generate labeled outerplanar graphs, we present a counting technique using the decomposition of a graph according to its block s ..."
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random instances. Outerplanar graphs are planar graphs with an embedding where every vertexlies on the outer face. They are interesting examples of combinatorial structures with respect to the mentioned motivations of random generation procedures,having numerous applications in various areas of computer
Dynamic ThreeDimensional Linear Programming
, 1992
"... We perform linear programming optimizations on the intersection of k polyhedra in R³, represented by their outer recursive decompositions, in expected time O(k log k log n + √k log k log³ n). We use this result to derive efficient algorithms for dynamic linear programming ..."
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Cited by 38 (5 self)
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We perform linear programming optimizations on the intersection of k polyhedra in R³, represented by their outer recursive decompositions, in expected time O(k log k log n + √k log k log³ n). We use this result to derive efficient algorithms for dynamic linear
Communicated by:
, 2010
"... Given an embedded planar acyclic digraph G, we define the problem of acyclic hamiltonian path completion with crossing minimization (acyclicHPCCM) to be the problem of determining a hamiltonian path completion set of edges such that, when these edges are embedded on G, they create thesmallest possi ..."
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possible numberofedgecrossings andturnGtoahamiltonian acyclic digraph. Our results include: 1. We provide a characterization under which a planar stdigraph G is hamiltonian. 2. For an outerplanar stdigraph G, we define the stPolygon decomposition of G and, based on its properties, we develop a linear
EFFICIENT PARALLEL ALGORITHMS FOR SHORTEST PATHS IN PLANAR DIGRAPHS
 BIT 32 (1992),215236
, 1992
"... Efficient parallel algorithms are presented, on the CREW PRAM model, for generating a succinct encoding of all pairs shortest path information in a directed planar graph G with realvalued edge costs but no negative cycles. We assume that a planar embedding of G is given, togetber with a set of q fa ..."
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Cited by 7 (4 self)
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previous one (M(n)). O(log 2 n) time, nprocessor algorithms are presented for various subproblems, including that of generating all pairs shortest path information in a directed outerplanar graph. Our work is based on the fundamental hammockdecomposition technique ofG. Frederickson. We achieve
1Network Coding in Planar Networks
"... Abstract—A basic problem in network coding is to choose a field to perform the encoding and decoding operations in. The main message we wish to deliver in this work is that while unboundedly large fields are required for linear algebraic codes in arbitrary networks, very small finite fields may be s ..."
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that coding over GF (3) is sufficient for all planar networks. The proof applies existing techniques in the literature, including multicast flow decomposition, graph coloring, as well as new techniques that made these tools readily applicable to all undirected planar multicast networks. We further show
Sampling Rooted 3Connected . . .
, 2006
"... In this thesis an algorithm for sampling rooted 3connected planar graphs (cnets) in deterministic polynomial time is presented. The algorithm is based on a decomposition strategy for cnets, which is formulated as a system of bijections between classes of cnets parameterized by the number of vert ..."
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In this thesis an algorithm for sampling rooted 3connected planar graphs (cnets) in deterministic polynomial time is presented. The algorithm is based on a decomposition strategy for cnets, which is formulated as a system of bijections between classes of cnets parameterized by the number
Approximately Counting Embeddings into Random Graphs
, 806
"... Let H be a graph, and let CH(G) be the number of (subgraph isomorphic) copies of H contained in a graph G. We investigate the fundamental problem of estimating CH(G). Previous results cover only a few specific instances of this general problem, for example, the case when H has degree at most one (mo ..."
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Cited by 2 (0 self)
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, subdivision of boundeddegree graphs, and major subclasses of outerplanar graphs, seriesparallel graphs and planar graphs, whereas unboundedwidth grid graphs are excluded. Additionally, our general technique can easily be applied to proving many more similar results. 1 1
Patient Specific Heart Models from High Resolution CT
"... Computer Tomography (CT) and in particular super fast, 64 and 256 detector CT has rapidly advanced over recent years, such that high resolution cardiac imaging has become a reality. In this paper, we provide a solution to the problem of automatically constructing three dimensional (3D) finiteelemen ..."
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Cited by 3 (1 self)
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artifacts (iii) a reconstruction of the inner and outer surface boundaries of the human heart and its chambers (iv) computation of the medial axis of the heart boundaries and a volumetric decomposition of the heart into tubular, planar and chunky regions, (v) a flexible match and fit of each
Patient Specic Heart Models from High Resolution CT
"... Computer Tomography (CT) and in particular super fast, 64 and 256 detector CT has rapidly advanced over recent years, such that high resolution cardiac imaging has become a reality. In this paper, we provide a solution to the problem of automatically constructing three dimensional (3D) niteelement ..."
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artifacts (iii) a reconstruction of the inner and outer surface boundaries of the human heart and its chambers (iv) computation of the medial axis of the heart boundaries and a volumetric decomposition of the heart into tubular, planar and chunky regions, (v) a exible match and t of each of the decomposed
1FlatCam: Thin, BareSensor Cameras using Coded Aperture and Computation
"... FlatCam is a thin formfactor lensless camera that consists of a coded mask placed on top of a bare, conventional sensor array. Unlike a traditional, lensbased camera where an image of the scene is directly recorded on the sensor pixels, each pixel in FlatCam records a linear combination of light f ..."
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FlatCam is a thin formfactor lensless camera that consists of a coded mask placed on top of a bare, conventional sensor array. Unlike a traditional, lensbased camera where an image of the scene is directly recorded on the sensor pixels, each pixel in FlatCam records a linear combination of light from multiple scene elements. A computational algorithm is then used to demultiplex the recorded measurements and reconstruct an image of the scene. FlatCam is an instance of a coded aperture imaging system; however, unlike the vast majority of related work, we place the coded mask extremely close to the image sensor that can enable a thin system. We employ a separable mask to ensure that both calibration and image reconstruction are scalable in terms of memory requirements and computational complexity. We demonstrate the potential of the FlatCam design using two prototypes: one at visible wavelengths and one at infrared wavelengths. I.
Results 11  20
of
25