1,353 research outputs found

    On hamiltonian colorings of block graphs

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    A hamiltonian coloring c of a graph G of order p is an assignment of colors to the vertices of G such that D(u,v)+c(u)c(v)p1D(u,v)+|c(u)-c(v)|\geq p-1 for every two distinct vertices u and v of G, where D(u,v) denoted the detour distance between u and v. The value hc(c) of a hamiltonian coloring c is the maximum color assigned to a vertex of G. The hamiltonian chromatic number, denoted by hc(G), is the min{hc(c)} taken over all hamiltonian coloring c of G. In this paper, we present a lower bound for the hamiltonian chromatic number of block graphs and give a sufficient condition to achieve the lower bound. We characterize symmetric block graphs achieving this lower bound. We present two algorithms for optimal hamiltonian coloring of symmetric block graphs.Comment: 12 pages, 1 figure. A conference version appeared in the proceedings of WALCOM 201

    On Metric Dimension of Functigraphs

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    The \emph{metric dimension} of a graph GG, denoted by dim(G)\dim(G), is the minimum number of vertices such that each vertex is uniquely determined by its distances to the chosen vertices. Let G1G_1 and G2G_2 be disjoint copies of a graph GG and let f:V(G1)V(G2)f: V(G_1) \rightarrow V(G_2) be a function. Then a \emph{functigraph} C(G,f)=(V,E)C(G, f)=(V, E) has the vertex set V=V(G1)V(G2)V=V(G_1) \cup V(G_2) and the edge set E=E(G1)E(G2){uvv=f(u)}E=E(G_1) \cup E(G_2) \cup \{uv \mid v=f(u)\}. We study how metric dimension behaves in passing from GG to C(G,f)C(G,f) by first showing that 2dim(C(G,f))2n32 \le \dim(C(G, f)) \le 2n-3, if GG is a connected graph of order n3n \ge 3 and ff is any function. We further investigate the metric dimension of functigraphs on complete graphs and on cycles.Comment: 10 pages, 7 figure

    Videoconferencing via satellite. Opening Congress to the people: Technical report

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    The feasibility of using satellite videoconferencing as a mechanism for informed dialogue between Congressmen and constituents to strengthen the legislative process was evaluated. Satellite videoconferencing was defined as a two-way interactive television with the TV signals transmitted by satellite. With videoconferencing, one or more Congressmen in Washington, D. C. can see, hear and talk with groups of citizens at distant locations around the country. Simultaneously, the citizens can see, hear and talk with the Congressmen

    Gully Formation at the Haughton Impact Structure (Arctic Canada) Through the Melting of Snow and Ground Ice, with Implications for Gully Formation on Mars

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    The formation of gullies on Mars has been the topic of active debate and scientific study since their first discovery by Malin and Edgett in 2000. Several mechanisms have been proposed to account for gully formation on Mars, from dry mass movement processes, release of water or brine from subsurface aquifers, and the melting of near-surface ground ice or snowpacks. In their global documentation of martian gullies, report that gullies are confined to ~2783S and ~2872N latitudes and span all longitudes. Gullies on Mars have been documented on impact crater walls and central uplifts, isolated massifs, and on canyon walls, with crater walls being the most common situation. In order to better understand gully formation on Mars, we have been conducting field studies in the Canadian High Arctic over the past several summers, most recently in summer 2018 and 2019 under the auspices of the Canadian Space Agency-funded Icy Mars Analogue Program. It is notable that the majority of previous studies in the Arctic and Antarctica, including our recent work on Devon Island, have focused on gullies formed on slopes generated by regular endogenic geological processes and in regular bedrock. How-ever, as noted above, meteorite impact craters are the most dominant setting for gullies on Mars. Impact craters provide an environment with diverse lithologies including impact-generated and impact-modified rocks and slope angle, and thus greatly variable hill slope processes could occur within a localized area. Here, we investigate the formation of gullies within the Haughton impact structure and compare them to gullies formed in unimpacted target rock in the nearby Thomas Lee Inle

    Spectral Measures of Bipartivity in Complex Networks

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    We introduce a quantitative measure of network bipartivity as a proportion of even to total number of closed walks in the network. Spectral graph theory is used to quantify how close to bipartite a network is and the extent to which individual nodes and edges contribute to the global network bipartivity. It is shown that the bipartivity characterizes the network structure and can be related to the efficiency of semantic or communication networks, trophic interactions in food webs, construction principles in metabolic networks, or communities in social networks.Comment: 16 pages, 1 figure, 1 tabl

    Self-organization of collaboration networks

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    We study collaboration networks in terms of evolving, self-organizing bipartite graph models. We propose a model of a growing network, which combines preferential edge attachment with the bipartite structure, generic for collaboration networks. The model depends exclusively on basic properties of the network, such as the total number of collaborators and acts of collaboration, the mean size of collaborations, etc. The simplest model defined within this framework already allows us to describe many of the main topological characteristics (degree distribution, clustering coefficient, etc.) of one-mode projections of several real collaboration networks, without parameter fitting. We explain the observed dependence of the local clustering on degree and the degree--degree correlations in terms of the ``aging'' of collaborators and their physical impossibility to participate in an unlimited number of collaborations.Comment: 10 pages, 8 figure

    SURF IA Conflict Detection and Resolution Algorithm Evaluation

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    The Enhanced Traffic Situational Awareness on the Airport Surface with Indications and Alerts (SURF IA) algorithm was evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. SURF IA is designed to increase flight crew situation awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the SURF IA algorithm under various runway scenarios, multiple levels of conflict detection and resolution (CD&R) system equipage, and various levels of horizontal position accuracy. This paper gives an overview of the SURF IA concept, simulation study, and results. Runway incursions are a serious aviation safety hazard. As such, the FAA is committed to reducing the severity, number, and rate of runway incursions by implementing a combination of guidance, education, outreach, training, technology, infrastructure, and risk identification and mitigation initiatives [1]. Progress has been made in reducing the number of serious incursions - from a high of 67 in Fiscal Year (FY) 2000 to 6 in FY2010. However, the rate of all incursions has risen steadily over recent years - from a rate of 12.3 incursions per million operations in FY2005 to a rate of 18.9 incursions per million operations in FY2010 [1, 2]. The National Transportation Safety Board (NTSB) also considers runway incursions to be a serious aviation safety hazard, listing runway incursion prevention as one of their most wanted transportation safety improvements [3]. The NTSB recommends that immediate warning of probable collisions/incursions be given directly to flight crews in the cockpit [4]

    On the Metric Dimension of Cartesian Products of Graphs

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    A set S of vertices in a graph G resolves G if every vertex is uniquely determined by its vector of distances to the vertices in S. The metric dimension of G is the minimum cardinality of a resolving set of G. This paper studies the metric dimension of cartesian products G*H. We prove that the metric dimension of G*G is tied in a strong sense to the minimum order of a so-called doubly resolving set in G. Using bounds on the order of doubly resolving sets, we establish bounds on G*H for many examples of G and H. One of our main results is a family of graphs G with bounded metric dimension for which the metric dimension of G*G is unbounded

    Beam Orientation Optimization for Intensity Modulated Radiation Therapy using Adaptive l1 Minimization

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    Beam orientation optimization (BOO) is a key component in the process of IMRT treatment planning. It determines to what degree one can achieve a good treatment plan quality in the subsequent plan optimization process. In this paper, we have developed a BOO algorithm via adaptive l_1 minimization. Specifically, we introduce a sparsity energy function term into our model which contains weighting factors for each beam angle adaptively adjusted during the optimization process. Such an energy term favors small number of beam angles. By optimizing a total energy function containing a dosimetric term and the sparsity term, we are able to identify the unimportant beam angles and gradually remove them without largely sacrificing the dosimetric objective. In one typical prostate case, the convergence property of our algorithm, as well as the how the beam angles are selected during the optimization process, is demonstrated. Fluence map optimization (FMO) is then performed based on the optimized beam angles. The resulted plan quality is presented and found to be better than that obtained from unoptimized (equiangular) beam orientations. We have further systematically validated our algorithm in the contexts of 5-9 coplanar beams for 5 prostate cases and 1 head and neck case. For each case, the final FMO objective function value is used to compare the optimized beam orientations and the equiangular ones. It is found that, our BOO algorithm can lead to beam configurations which attain lower FMO objective function values than corresponding equiangular cases, indicating the effectiveness of our BOO algorithm.Comment: 19 pages, 2 tables, and 5 figure

    Edge Partitions of Optimal 22-plane and 33-plane Graphs

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    A topological graph is a graph drawn in the plane. A topological graph is kk-plane, k>0k>0, if each edge is crossed at most kk times. We study the problem of partitioning the edges of a kk-plane graph such that each partite set forms a graph with a simpler structure. While this problem has been studied for k=1k=1, we focus on optimal 22-plane and 33-plane graphs, which are 22-plane and 33-plane graphs with maximum density. We prove the following results. (i) It is not possible to partition the edges of a simple optimal 22-plane graph into a 11-plane graph and a forest, while (ii) an edge partition formed by a 11-plane graph and two plane forests always exists and can be computed in linear time. (iii) We describe efficient algorithms to partition the edges of a simple optimal 22-plane graph into a 11-plane graph and a plane graph with maximum vertex degree 1212, or with maximum vertex degree 88 if the optimal 22-plane graph is such that its crossing-free edges form a graph with no separating triangles. (iv) We exhibit an infinite family of simple optimal 22-plane graphs such that in any edge partition composed of a 11-plane graph and a plane graph, the plane graph has maximum vertex degree at least 66 and the 11-plane graph has maximum vertex degree at least 1212. (v) We show that every optimal 33-plane graph whose crossing-free edges form a biconnected graph can be decomposed, in linear time, into a 22-plane graph and two plane forests
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