29 research outputs found

    Circumference of 3-connected claw-free graphs and large Eulerian subgraphs of 3-edge-connected graphs

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    AbstractThe circumference of a graph is the length of its longest cycles. Results of Jackson, and Jackson and Wormald, imply that the circumference of a 3-connected cubic n-vertex graph is Ω(n0.694), and the circumference of a 3-connected claw-free graph is Ω(n0.121). We generalize and improve the first result by showing that every 3-edge-connected graph with m edges has an Eulerian subgraph with Ω(m0.753) edges. We use this result together with the Ryjáček closure operation to improve the lower bound on the circumference of a 3-connected claw-free graph to Ω(n0.753). Our proofs imply polynomial time algorithms for finding large Eulerian subgraphs of 3-edge-connected graphs and long cycles in 3-connected claw-free graphs

    Emotional State Classification and Related Behaviors Among Cyber Attackers

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    Cyber deception is a strategy that defenders can leverage to gain an advantage over cyber attackers. The effects of deception on the attacker however, are not yet well understood. Quantifying the tangible and emotional effects of deception on the attacker’s performance, beliefs, and emotional state are critical to deploying effective, targeted cyber deception. Our work uses data from a human-subjects experiment measuring the impact of cyber and psychological deception on over 100 professional red-teamers. These results demonstrate that an attacker’s cognitive and emotional state can often be inferred from data already observed and collected by cyber defenders world-wide. Future work will leverage this observed data-set to formulate more informed defensive strategies

    Bandwidth of trees of diameter at most 4

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    For a graph G, let γ:V(G)→1,⋯,|V(G)| be a one-to-one function. The bandwidth of γ is the maximum of |γ(u)-γ(v)| over uv∈E(G). The bandwidth of G, denoted b(G), is the minimum bandwidth over all embeddings γ, b(G)=min γmax|γ(u)-γ(v) |:uv∈E(G). In this paper, we show that the bandwidth computation problem for trees of diameter at most 4 can be solved in polynomial time. This naturally complements the result computing the bandwidth for 2-caterpillars. © 2012 Elsevier B.V. All rights reserved

    HRTF Magnitude Synthesis via Sparse Representation of Anthropometric Features

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    International audienceWe propose a method for the synthesis of the magnitudes of Head-related Transfer Functions (HRTFs) using a sparse representation of anthropometric features.Our approach treats the HRTF synthesis problem as finding a sparse representation of the subject's anthropometric features w.r.t. the anthropometric features in the training set.The fundamental assumption is that the magnitudes of a given HRTF set can be described by the same sparse combination as the anthropometric data.Thus, we learn a sparse vector that represents the subject's anthropometric features as a linear superposition of the anthropometric features of a small subset of subjects from the training data.Then, we apply the same sparse vector directly on the HRTF tensor data.For evaluation purpose we use a new dataset, containing both anthropometric features and HRTFs.We compare the proposed sparse representation based approach with ridge regression and with the data of a manikin (which was designed based on average anthropometric data), and we simulate the best and the worst possible classifiers to select one of the HRTFs from the dataset.For instrumental evaluation we use log-spectral distortion.Experiments show that our sparse representation outperforms all other evaluated techniques, and that the synthesized HRTFs are almost as good as the best possible HRTF classifier

    Parallel altitudinal clines reveal trends in adaptive evolution of genome size in \u3ci\u3eZea mays\u3c/i\u3e

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    While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes

    Approximating the circumference of 3-connected claw-free graphs

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    Jackson and Wormald show that every 3-connected K_1,d-free graph, on n vertices, contains a cycle of length at least 1/2 n^g(d) where g(d) = (log_2 6 + 2 log_2 (2d+1))^-1. For d = 3, g(d) ~ 0.122. Improving this bound, we prove that if G is a 3-connected claw-free graph on at least 6 vertices, then there exists a cycle C in G such that |E(C)| is at least c n^g+5, where g = log_3 2 and c > 1/7 is a constant. To do this, we instead prove a stronger theorem that requires the cycle to contain two specified edges. We then use Tutte decomposition to partition the graph and then use the inductive hypothesis of our theorem to find paths or cycles in the different parts of the decomposition.Ph.D.Committee Chair: Yu, Xingxing; Committee Member: Duke, Richard; Committee Member: Tetali, Prasad; Committee Member: Thomas, Robin; Committee Member: Vigoda, Eri

    On the Reconstruction of Planar Graphs

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    We show that the planarity of a graph can be recognized from its vertex deleted subgraphs, which answers a question posed by Bondy and Hemminger in 1979. We also state some useful counting lemmas and use them to reconstruct certain planar graphs

    Rates of abiotic Mn^(II) oxidation by O₂: Influence of various multidentate ligands at high pH

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    Oxidn. of manganous manganese (Mn^(II)) is an important process driving manganese cycles in natural aquatic systems and leading to the formation of solid-phase Mn^(III,IV) (hydr)oxide products. Previous research has shown that some simple ligands (e.g., phosphate, sulfate, chloride, fluoride) can bind with Mn^(II) to make it unreactive to oxidn. by dissolved oxygen. However, there is little to no understanding of the role played by strong, complex-forming ligands in Mn^(II) oxidn. reactions. The objective of this study was to evaluate the rates of abiotic Mn^(II) oxidn. by O₂ in the presence of several strong complex-forming ligands (pyrophosphate, tripolyphosphate, EDTA, oxalate) in bicarbonate-carbonate buffered lab. solns. of pH 9.42, 9.65 and 10.19. The influence of increasing ligand concns. on obsd. autocatalytic patterns of Mn^(II) oxidn. was investigated, and initial oxidn. rates have been tentatively linked to the initial Mn^(II) speciation in exptl. solns. Obsd. rates of Mn^(II) oxidn. decreased with increasing ligand concn. for all four ligands tested. However, the profiles obsd. and the magnitudes of decrease in initial oxidn. rates were different for the different ligands. Likely explanations for these observations include the denticity of the tested ligands, the relative strength of the ligands to complex Mn^(II) vs. Mn^(III), and the ability of some ligands to act as an electron donor and thereby enhance the back reaction
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