Showing 641 - 660 results of 821 for search '"random graph"', query time: 0.17s Refine Results
  1. 641

    Participatory approaches and Social Network Analysis to analyse the emergence of collective action for rural development: a case study in the Spanish Pyrenees by M. Teston, E. Sturaro, E. Muñoz-Ulecia, A. Tenza-Peral, S. Raniolo, E. Pisani, C. Pachoud, M. Ramanzin, D. Martín-Collado

    Published 2024-12-01
    “…The trust network was analysed using the Louvain’s algorithm to identify potential internal communities and the exponential random graph model (ERGM) to infer the shaping effects of actors’ attributes on the network’s structure. …”
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    Article
  2. 642

    A social network analysis model approach to understand tuberculosis transmission in remote rural Madagascar by Christine Pando, Ashley Hazel, Lai Yu Tsang, Kimmerling Razafindrina, Andry Andriamiadanarivo, Roger Mario Rabetombosoa, Ideal Ambinintsoa, Gouri Sadananda, Peter M. Small, Astrid M. Knoblauch, Niaina Rakotosamimanana, Simon Grandjean Lapierre

    Published 2023-08-01
    “…Network- and individual-level characteristics determining contact formation and structure were identified by fitting an exponential random graph model (ERGM), which formed the basis of the contact structure and model dynamics. …”
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    Article
  3. 643
  4. 644

    Connectivity and Equilibrium in Random Games by Daskalakis, Constantinos, Dimakis, Alexandros G., Mossel, Elchanan

    Published 2012
    “…In order to obtain a refined characterization of the degree of connectivity associated with the existence of equilibria, we also study the model in the random graph setting. In particular, we look at the case where the interaction graph is drawn from the Erdős–Rényi, G(n, p), model where each edge is present independently with probability p. …”
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    Article
  5. 645

    Topics in additive combinatorics by Mrazovic, R

    Published 2016
    “…We prove that if we sample such a random graph independently for every prime, then almost surely (i) for infinitely many primes <em>p</em> the clique number is Ω(log <em>p</em> log log <em>p</em>), whilst (ii) for almost all primes the clique number is (2 + <em>o</em>(1)) log <em>p</em>.…”
    Thesis
  6. 646

    Development of Social Support Networks by Patients With Depression Through Online Health Communities: Social Network Analysis by Lu, Yingjie, Luo, Shuwen, Liu, Xuan

    Published 2021-01-01
    “…MethodsWe used social network theory and constructed exponential random graph models to help understand the informational and emotional support networks in online depression communities. …”
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    Article
  7. 647

    Asymmetric particle systems and last-passage percolation in one and two dimensions by Schmidt, P

    Published 2012
    “…</p> <p>The second model we study is directed last-passage percolation on the random graph <em>G</em> = (<em>V,E</em>) where <em>V</em> = &amp;Zopf; and each edge (<em>i,j</em>), for <em>i</em> &amp;LT;: <em>j</em> ∈ , is present in <em>E</em> independently with some probability <em>p</em> ∈ (0,1]. …”
    Thesis
  8. 648

    Local access to huge random objects through partial sampling by Yodpinyanee, Anak, Rubinfeld, Ronitt, Biswas, Amartya Shankha

    Published 2021
    “…As in previous local-access implementations for random graphs, we support Vertex-Pair and Next-Neighbor queries. …”
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    Article
  9. 649

    Livestock Network Analysis for Rhodesiense Human African Trypanosomiasis Control in Uganda by Walter O. Okello, Walter O. Okello, Christine A. Amongi, Christine A. Amongi, Dennis Muhanguzi, Ewan T. MacLeod, Charles Waiswa, Charles Waiswa, Charles Waiswa, Alexandra P. Shaw, Alexandra P. Shaw, Susan C. Welburn, Susan C. Welburn

    Published 2021-06-01
    “…This study explores livestock movement data to describe cattle trade network topology and assess the effects of disease control interventions on the transmission of rHAT infectiousness.Methods: Network analysis was used to generate a cattle trade network with livestock data which was collected from cattle traders (n = 197) and validated using random graph methods. Additionally, the cattle trade network was combined with a susceptible, infected, recovered (SIR) compartmental model to simulate spread of rHAT (Ro 1.287), hence regarded as “slow” pathogen, and evaluate the effects of disease interventions.Results: The cattle trade network exhibited a low clustering coefficient (0.5) with most cattle markets being weakly connected and a few being highly connected. …”
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    Article
  10. 650

    Telehealth Use Following COVID-19 Within Patient-Sharing Physician Networks at a Rural Comprehensive Cancer Center: Cross-sectional Analysis by Liyang Yu, You-Chi Liu, Sarah L Cornelius, Bruno T Scodari, Gabriel A Brooks, Alistair James O'Malley, Tracy Onega, Erika L Moen

    Published 2023-01-01
    “…Exponential-family random graph models were performed to estimate homophily terms for the likelihood of ties existing between physicians colocated at the hub comprehensive cancer center. …”
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    Article
  11. 651

    Entropy Related to <i>K</i>-Banhatti Indices via Valency Based on the Presence of <i>C</i><sub>6</sub><i>H</i><sub>6</sub> in Various Molecules by Muhammad Usman Ghani, Francis Joseph H. Campena, Muhammad Kashif Maqbool, Jia-Bao Liu, Sanaullah Dehraj, Murat Cancan, Fahad M. Alharbi

    Published 2023-01-01
    “…Shannon’s entropy metric is applied to represent a random graph’s variability. Entropy is a thermodynamic function in physics that, based on the variety of possible configurations for molecules to take, describes the randomness and disorder of molecules in a given system or process. …”
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    Article
  12. 652

    Impact of post-incarceration care engagement interventions on HIV transmission among young Black men who have sex with men and their sexual partners: an agent-based network modelin... by Anna L. Hotton, Francis Lee, Daniel Sheeler, Jonathan Ozik, Nicholson Collier, Mert Edali, Babak Mahdavi Ardestani, Russell Brewer, Katrina M. Schrode, Kayo Fujimoto, Nina T. Harawa, John A. Schneider, Aditya S. Khanna

    Published 2023-12-01
    “…Methods: Exponential random graph models were used to model network formation and dissolution dynamics, and network dynamics and HIV care continuum engagement were varied according to incarceration status. …”
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    Article
  13. 653
  14. 654

    Limits of Latin squares by Frederik Garbe, Robert Hancock, Jan Hladky, Maryam Sharifzadeh

    Published 2023-07-01
    “…This can be well approximated by a random graph with edge probability 1/2. Similarly, if we consider the uniform measure on $[0,1]^2$ as a permuton, it is well approximated by a random permutation. …”
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    Article
  15. 655

    Weighted hypersoft configuration model by Ivan Voitalov, Pim van der Hoorn, Maksim Kitsak, Fragkiskos Papadopoulos, Dmitri Krioukov

    Published 2020-10-01
    “…If the degree sequence is constrained exactly, the corresponding microcanonical ensemble of random graphs with a given degree sequence is the configuration model per se. …”
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    Article
  16. 656
  17. 657

    Hierarchy Depth in Directed Networks by Krzysztof Suchecki, Janusz A. Hołyst

    Published 2022-02-01
    “…The behavior of the two depth measures is investigated in Erdös-Rényi random graphs, directed Barabási-Albert networks, and in Gnutella p2p share network. …”
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    Article
  18. 658
  19. 659

    A sequence of triangle-free pseudorandom graphs by Conlon, D

    Published 2016
    “…A construction of Alon yields a sequence of highly pseudorandom triangle-free graphs with edge density significantly higher than one might expect from comparison with random graphs. We give an alternative construction for such graphs.…”
    Journal article
  20. 660