Zobrazeno 1 - 10
of 972
pro vyhledávání: '"Sokolsky P"'
Autor:
Park, Jean, Pugh, Sydney, Sridhar, Kaustubh, Liu, Mengyu, Yarna, Navish, Kaur, Ramneet, Dutta, Souradeep, Bernardis, Elena, Sokolsky, Oleg, Lee, Insup
Large Deep Neural Networks (DNNs) are often data hungry and need high-quality labeled data in copious amounts for learning to converge. This is a challenge in the field of medicine since high quality labeled data is often scarce. Data programming has
Externí odkaz:
http://arxiv.org/abs/2407.07982
Autor:
Telescope Array Collaboration, Abbasi, R. U., Abe, Y., Abu-Zayyad, T., Allen, M., Arai, Y., Arimura, R., Barcikowski, E., Belz, J. W., Bergman, D. R., Blake, S. A., Buckland, I., Cheon, B. G., Chikawa, M., Fujii, T., Fujisue, K., Fujita, K., Fujiwara, R., Fukushima, M., Furlich, G., Globus, N., Gonzalez, R., Hanlon, W., Hayashida, N., He, H., Hibi, R., Hibino, K., Higuchi, R., Honda, K., Ikeda, D., Inoue, N., Ishii, T., Ito, H., Ivanov, D., Iwasaki, A., Jeong, H. M., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kasami, S., Kawakami, S., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kimura, Y., Komae, I., Kuzmin, V., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lubsandorzhiev, B., Lundquist, J. P., Matsumiya, H., Matsuyama, T., Matthews, J. N., Mayta, R., Mizuno, K., Murakami, M., Myers, I., Nagataki, S., Nakai, K., Nakamura, T., Nishio, E., Nonaka, T., Oda, H., Ogio, S., Onishi, M., Ohoka, H., Okazaki, N., Oku, Y., Okuda, T., Omura, Y., Ono, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Pshirkov, M. S., Remington, J., Rodriguez, D. C., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Saito, R., Sakaki, N., Sako, T., Sakurai, N., Sato, D., Sato, K., Sato, S., Sekino, K., Shah, P. D., Shibata, N., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinto, D., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Udo, S., Urban, F., Warren, D., Wong, T., Yamazaki, K., Yashiro, K., Yoshida, F., Zhezher, Y., Zundel, Z.
We report an estimation of the injected mass composition of ultra-high energy cosmic rays (UHECRs) at energies higher than 10 EeV. The composition is inferred from an energy-dependent sky distribution of UHECR events observed by the Telescope Array s
Externí odkaz:
http://arxiv.org/abs/2406.19287
Autor:
Telescope Array Collaboration, Abbasi, R. U., Abe, Y., Abu-Zayyad, T., Allen, M., Arai, Y., Arimura, R., Barcikowski, E., Belz, J. W., Bergman, D. R., Blake, S. A., Buckland, I., Cheon, B. G., Chikawa, M., Fujii, T., Fujisue, K., Fujita, K., Fujiwara, R., Fukushima, M., Furlich, G., Globus, N., Gonzalez, R., Hanlon, W., Hayashida, N., He, H., Hibi, R., Hibino, K., Higuchi, R., Honda, K., Ikeda, D., Inoue, N., Ishii, T., Ito, H., Ivanov, D., Iwasaki, A., Jeong, H. M., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kasami, S., Kawakami, S., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kimura, Y., Komae, I., Kuzmin, V., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lubsandorzhiev, B., Lundquist, J. P., Matsumiya, H., Matsuyama, T., Matthews, J. N., Mayta, R., Mizuno, K., Murakami, M., Myers, I., Nagataki, S., Nakai, K., Nakamura, T., Nishio, E., Nonaka, T., Oda, H., Ogio, S., Onishi, M., Ohoka, H., Okazaki, N., Oku, Y., Okuda, T., Omura, Y., Ono, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Pshirkov, M. S., Remington, J., Rodriguez, D. C., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Saito, R., Sakaki, N., Sako, T., Sakurai, N., Sato, D., Sato, K., Sato, S., Sekino, K., Shah, P. D., Shibata, N., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinto, D., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Udo, S., Urban, F., Warren, D., Wong, T., Yamazaki, K., Yashiro, K., Yoshida, F., Zhezher, Y., Zundel, Z.
We use a new method to estimate the injected mass composition of ultrahigh cosmic rays (UHECRs) at energies higher than 10 EeV. The method is based on comparison of the energy-dependent distribution of cosmic ray arrival directions as measured by the
Externí odkaz:
http://arxiv.org/abs/2406.19286
Autor:
The Telescope Array Collaboration, Abbasi, R. U., Abu-Zayyad, T., Allen, M., Belz, J. W., Bergman, D. R., Buckland, I., Campbell, W., Cheon, B. G., Endo, K., Fedynitch, A., Fujii, T., Fujisue, K., Fujita, K., Fukushima, M., Furlich, G., Gerber, Z., Globus, N., Hanlon, W., Hayashida, N., He, H., Hibino, K., Higuchi, R., Ikeda, D., Ishii, T., Ivanov, D., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kawachi, Y., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kobo, R., Komae, I., Komatsu, K., Komori, K., Koyama, C., Kudenko, M., Kuroiwa, M., Kusumori, Y., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lee, M. J., Lubsandorzhiev, B., Lundquist, J. P., Matsuzawa, A., Matthews, J. A., Matthews, J. N., Mizuno, K., Mori, M., Murakami, M., Nagataki, S., Nakahara, M., Nakamura, T., Nakayama, T., Nakayama, Y., Nonaka, T., Ogio, S., Ohoka, H., Okazaki, N., Onishi, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Przybylak, M., Pshirkov, M. S., Remington, J., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Sakaki, N., Sakamoto, R., Sako, T., Sakurai, N., Sakurai, S., Sato, D., Sato, S., Sekino, K., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinozaki, K., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tomida, T., Troitsky, S., Tsunesada, Y., Udo, S., Urban, F., Vaiman, I. A., Vrábel, M., Warren, D., Yamazaki, K., Zhezher, Y., Zundel, Z., Zvirzdin, J.
We report on an observation of the difference between northern and southern skies of the ultrahigh energy cosmic ray energy spectrum with a significance of ${\sim}8\sigma$. We use measurements from the two largest experiments$\unicode{x2014}$the Tele
Externí odkaz:
http://arxiv.org/abs/2406.08612
Autor:
Sokolsky Pierre
Publikováno v:
EPJ Web of Conferences, Vol 283, p 01003 (2023)
I describe the history of the use of the air-fluorescence technique in UHECR physics.
Externí odkaz:
https://doaj.org/article/b4294b610d774b3b955bb4731bd77671
Autor:
Lu, Pengyuan, Zhang, Lin, Liu, Mengyu, Sridhar, Kaustubh, Kong, Fanxin, Sokolsky, Oleg, Lee, Insup
Publikováno v:
ACM Computing Surveys 1 (2024) 1-31
Cyber-physical systems (CPS) have experienced rapid growth in recent decades. However, like any other computer-based systems, malicious attacks evolve mutually, driving CPS to undesirable physical states and potentially causing catastrophes. Although
Externí odkaz:
http://arxiv.org/abs/2404.04472
Autor:
Glinsky, Alex, Sokolsky, Alexey
It is evident that, currently, generative models are surpassed in quality by human professionals. However, with the advancements in Artificial Intelligence, this gap will narrow, leading to scenarios where individuals who have dedicated years of thei
Externí odkaz:
http://arxiv.org/abs/2403.09700
Autor:
Zheng, Xi, Mok, Aloysius K., Piskac, Ruzica, Lee, Yong Jae, Krishnamachari, Bhaskar, Zhu, Dakai, Sokolsky, Oleg, Lee, Insup
The integration of machine learning (ML) into cyber-physical systems (CPS) offers significant benefits, including enhanced efficiency, predictive capabilities, real-time responsiveness, and the enabling of autonomous operations. This convergence has
Externí odkaz:
http://arxiv.org/abs/2311.07377
Learning-enabled controllers have been adopted in various cyber-physical systems (CPS). When a learning-enabled controller fails to accomplish its task from a set of initial states, researchers leverage repair algorithms to fine-tune the controller's
Externí odkaz:
http://arxiv.org/abs/2311.03477
Autor:
Dutta, Souradeep, Caprio, Michele, Lin, Vivian, Cleaveland, Matthew, Jang, Kuk Jin, Ruchkin, Ivan, Sokolsky, Oleg, Lee, Insup
A particularly challenging problem in AI safety is providing guarantees on the behavior of high-dimensional autonomous systems. Verification approaches centered around reachability analysis fail to scale, and purely statistical approaches are constra
Externí odkaz:
http://arxiv.org/abs/2308.14815