- Jan 2023
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hypothes.is hypothes.is假设1
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个人学习可能取决于他人行为的主张突出了将学习环境视为一个涉及多个互动参与者的系统的重要性
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- Dec 2022
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The connectionless configuration of IS0protocols has also been colored by the history of theInternet suite, so an understanding ‘of the Internet designphilosophy may be helpful to those working with ISO.
ISO protocols
At one point, the Open Systems Interconnection model (OSI model) was the leading contender for the network standard. It didn't survive in competition with the more nimble TCP/IP stack design.
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- Dec 2021
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arxiv.org arxiv.org
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Kan, U., Feng, M., & Porter, M. A. (2021). An Adaptive Bounded-Confidence Model of Opinion Dynamics on Networks. ArXiv:2112.05856 [Physics]. http://arxiv.org/abs/2112.05856
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- Jul 2021
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link.aps.org link.aps.org
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Wang, B., Gou, M., Guo, Y., Tanaka, G., & Han, Y. (2020). Network structure-based interventions on spatial spread of epidemics in metapopulation networks. Physical Review E, 102(6), 062306. https://doi.org/10.1103/PhysRevE.102.062306
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Ingale, M., & Shekatkar, S. M. (2020). Resource dependency and survivability in complex networks. Physical Review E, 102(6), 062304. https://doi.org/10.1103/PhysRevE.102.062304
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Ortiz, E., & Serrano, M. Á. (2021). Multiscale opinion dynamics on real networks. ArXiv:2107.06656 [Physics]. http://arxiv.org/abs/2107.06656
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- May 2021
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journals.plos.org journals.plos.org
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Piotrowska, M. J., Sakowski, K., Karch, A., Tahir, H., Horn, J., Kretzschmar, M. E., & Mikolajczyk, R. T. (2020). Modelling pathogen spread in a healthcare network: Indirect patient movements. PLOS Computational Biology, 16(11), e1008442. https://doi.org/10.1371/journal.pcbi.1008442
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- Apr 2021
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www.kickstarter.com www.kickstarter.com
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Only the Starter Kit is available in this reboot. The Starter Kit is FREE, in order to distribute it as widely as possible. This goal of this Kickstarter campaign is to introduce Clash of Deck to the whole word and to bring a community together around the game. If the Kickstarter campaign succeeds, we will then have the necessary dynamic to publish additional paid content on a regular basis, to enrich the game with: stand-alone expansions, additional modules, alternative game modes..
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- Mar 2021
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arxiv.org arxiv.org
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Di Lauro, F., Berthouze, L., Dorey, M. D., Miller, J. C., & Kiss, I. Z. (2020). The impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: A mean-field model perspective. ArXiv:2007.06975 [Physics, q-Bio]. http://arxiv.org/abs/2007.06975
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- Feb 2021
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link.aps.org link.aps.org
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Wang, X., Sirianni, A. D., Tang, S., Zheng, Z., & Fu, F. (2020). Public Discourse and Social Network Echo Chambers Driven by Socio-Cognitive Biases. Physical Review X, 10(4), 041042. https://doi.org/10.1103/PhysRevX.10.041042
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Hickok, A., Kureh, Y., Brooks, H. Z., Feng, M., & Porter, M. A. (2021). A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs. ArXiv:2102.06825 [Nlin, Physics:Physics]. http://arxiv.org/abs/2102.06825
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- Aug 2020
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Alfaro, L., Faia, E., Lamersdorf, N., & Saidi, F. (2020). Social Interactions in Pandemics: Fear, Altruism, and Reciprocity (Working Paper No. 27134; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27134
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- Jul 2020
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www.nber.org www.nber.org
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Baqaee, D., & Farhi, E. (2020). Nonlinear Production Networks with an Application to the Covid-19 Crisis (Working Paper No. 27281; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27281
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www.nber.org www.nber.org
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Fajgelbaum, P., Khandelwal, A., Kim, W., Mantovani, C., & Schaal, E. (2020). Optimal Lockdown in a Commuting Network (Working Paper No. 27441; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27441
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www.nature.com www.nature.com
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Block, P., Hoffman, M., Raabe, I. J., Dowd, J. B., Rahal, C., Kashyap, R., & Mills, M. C. (2020). Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world. Nature Human Behaviour, 4(6), 588–596. https://doi.org/10.1038/s41562-020-0898-6
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arxiv.org arxiv.org
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Gupta, H., & Porter, M. A. (2020). Mixed Logit Models and Network Formation. ArXiv:2006.16516 [Physics, Stat]. http://arxiv.org/abs/2006.16516
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- Jun 2020
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Zhang, L., & Peixoto, T. P. (2020). Statistical inference of assortative community structures. ArXiv:2006.14493 [Cond-Mat, Physics:Physics, Stat]. http://arxiv.org/abs/2006.14493
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www.researchgate.net www.researchgate.net
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Mclachlan, S., Lucas, P., Kudakwashe Dube, Hitman, G. A., Osman, M., Kyrimi, E., Neil, M., & Fenton, N. E. (2020). The fundamental limitations of COVID-19 contact tracing methods and how to resolve them with a Bayesian network approach. https://doi.org/10.13140/RG.2.2.27042.66243
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- COVID-19
- contact tracing
- containment
- lang:en
- Bayesian
- prediction
- limitation
- app
- digital solution
- network model
- likelihood
- is:preprint
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arxiv.org arxiv.org
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Cai, L., Chen, Z., Luo, C., Gui, J., Ni, J., Li, D., & Chen, H. (2020). Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs. ArXiv:2005.07427 [Cs, Stat]. http://arxiv.org/abs/2005.07427
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- May 2020
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psyarxiv.com psyarxiv.com
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Golino, H., Christensen, A. P., Moulder, R. G., Kim, S., & Boker, S. M. (2020, April 14). Modeling latent topics in social media using Dynamic Exploratory Graph Analysis: The case of the right-wing and left-wing trolls in the 2016 US elections. https://doi.org/10.31234/osf.io/tfs7c
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link.aps.org link.aps.org
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Krönke, J., Wunderling, N., Winkelmann, R., Staal, A., Stumpf, B., Tuinenburg, O. A., & Donges, J. F. (2020). Dynamics of tipping cascades on complex networks. Physical Review E, 101(4), 042311. https://doi.org/10.1103/PhysRevE.101.042311
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- Jan 2018
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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