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Muography. Группа авторовЧитать онлайн книгу.

Muography - Группа авторов


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H. K. M. (2015). Muographic mapping of the subsurface density structures in Miura, Boso and Izu peninsulas, Japan. Scientific Reports, 5, 8305. https://doi.org/10.1038/srep08305

      69 Tanaka, H. K. M., Kusagaya, T., & Shinohara, H. (2014). Radiographic visualization of magma dynamics in an erupting volcano. Nature Communications, 5, 3381. https://doi.org/10.1038/ncomms4381

      70 Tanaka, H. K. M., Nakano, T., Takahashi, S., Yoshida, J., Takeo, M., Oikawa, J., et al. (2007). High resolution imaging in the inhomogeneous crust with cosmic‐ray muon radiography: The density structure below the volcanic crater floor of Mt. Asama, Japan. Earth and Planetary Science Letters, 263, 104–113. https://doi.org/10.1016/j.epsl.2007.09.001

      71 Tanaka, H. K. M., Taira, H., Uchida, T., Tanaka, M., Takeo, M., Ohminato, T., et al. (2010). Three‐dimensional computational axial tomography scan of a volcano with cosmic ray muon radiography. Journal of Geophysical Research, 115, B12332. https://doi.org/10.1029/2010JB007677

      72 Tensorflow (2020). Retrieved from https://tensorflow.org/

      73 Titov, V. V., Gonzalez, F. I., Bernard, E. N., Eble, M. C., Mofjeld, H. O., Newman, J. C., & Venturato, A. J. (2005). Real‐time tsunami forecasting: Challenges and solutions. Natural Hazards, 35, 35–41. https://doi.org/10.1007/s11069‐004‐2403‐3

      74 Vapnik, V. N. (1995). The Nature of Statistical Learning Theory. Springer‐Verlag, New York.

      75 VanderPlas, J., A., Connolly, J., Ivezić, Z., & Gray, A. (2012). Introduction to astroML: Machine learning for astrophysics. Conference on Intelligent Data Understanding, 2012, 47–54.

      76 Varga, D., Gál, Z., Hamar, G., Molnár, J. S., Oláh, É., & Pázmándi, P. (2015). Cosmic muon detector using proportional chambers. European Journal of Physics, 36, 065006. https://doi.org/10.1088/0143‐0807/36/6/065006

      77 Varga, D., Hamar, G., & Oláh, L. (2021). Development of multi‐wire proportional chamber‐based trackers for muography. In: L. Oláh, H. K. M. Tanaka, D. Varga (Eds.), Muography: Exploring Earth’s Subsurface With Elementary Particles, Geophysical Monograph Series 270, Washington, DC: American Geophysical Union. (this volume)

      78 Varga, D., Nyitrai, G., Hamar, G., Galgóczi, G., Oláh, L., Tanaka, H. K. M., & Ohminato, T. (2020). Detector developments for high performance muography applications. Nuclear Instruments and Methods in Physics Research Section A, 958, 162236. https://doi.org/10.1016/j.nima.2019.05.077

      79 Varga, D., Nyitrai, G., Hamar, G., & Oláh, L. (2016). High efficiency gaseous tracking detector for cosmic muon radiography. Advances in High Energy Physics, 2016, 1962317. https://doi.org/10.1155/2016/1962317

      80 Witsil, A. J. C. & Johnson, J. B. (2020). Volcano video data characterized and classified using computer vision and machine learning algorithms. Geoscience Frontiers, 11, 1789–1803. https://doi.org/10.1016/j.gsf.2020.01.016

      81 Yamaoka, K., Geshi, N., Hashimoto, T., Ingrebitsen, S. E., & Oikawa, T. (2016). Special issue “The phreatic eruption of Mt. Ontake volcano in 2014”. Earth, Planets and Space, 68, 175. https://doi.org/10.1186/s40623‐016‐0548‐4

      82 Youden, W. J. (1950). Index for rating diagnostics tests. Cancer, 3, 32–35. https://doi.org/10.1002/1097‐0142(1950)3:1<32::aid‐cncr2820030106>3.0.co;2‐3

Part II Muography for Volcanic Investigations

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