Zobrazeno 1 - 10
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pro vyhledávání: '"Chin BY"'
This paper is a preliminary study on the security and design of cryptosystems using Gabidulin-Kronecker Product Codes. In particular, we point out the design impracticality of the system, and propose ways to improve it.
Externí odkaz:
http://arxiv.org/abs/2410.06849
Autor:
Stuyck, Tuur, Lin, Gene Wei-Chin, Larionov, Egor, Chen, Hsiao-yu, Bozic, Aljaz, Sarafianos, Nikolaos, Roble, Doug
Realistic hair motion is crucial for high-quality avatars, but it is often limited by the computational resources available for real-time applications. To address this challenge, we propose a novel neural approach to predict physically plausible hair
Externí odkaz:
http://arxiv.org/abs/2412.10061
Imitation learning is a data-driven approach to learning policies from expert behavior, but it is prone to unreliable outcomes in out-of-sample (OOS) regions. While previous research relying on stable dynamical systems guarantees convergence to a des
Externí odkaz:
http://arxiv.org/abs/2412.07544
It has been recognized that the impulsive noise (IN) generated by power devices poses significant challenges to wireless receivers in practice. In this paper, we assess the achievable information rate (AIR) and the performance of practical turbo rece
Externí odkaz:
http://arxiv.org/abs/2412.07911
Blind estimation of intersymbol interference channels based on the Baum-Welch (BW) algorithm, a specific implementation of the expectation-maximization (EM) algorithm for training hidden Markov models, is robust and does not require labeled data. How
Externí odkaz:
http://arxiv.org/abs/2412.07907
Autor:
Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Bargemann, J. W., Barillier, E. E., Bauer, D., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Coronel, R., Cottle, A., Cox, G., Curran, D., Dahl, C. E., Darlington, I., Dave, S., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Dubey, S., Eriksen, S. R., Fan, A., Fayer, S., Fearon, N. M., Fieldhouse, N., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Ghosh, A., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. J., Hall, C. R., Hall, T. J., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., K., Meghna K., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kim, Y. D., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Lawes, C., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McLaughlin, J. B., McMonigle, R., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., O'Brien, C. L., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Oyulmaz, K. Y, Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Richards, A., Riffard, Q., Rischbieter, G. R. C., Ritchey, E., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Sehr, G., Shafer, B., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Usón, A., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Weeldreyer, L., Whitis, T. J., Wild, K., Williams, M., Wisniewski, W. J., Wolf, L., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xu, J., Xu, Y., Yeh, M., Yeum, D., Zha, W., Zweig, E. A.
We report on a search for millicharged particles (mCPs) produced in cosmic ray proton atmospheric interactions using data collected during the first science run of the LUX-ZEPLIN experiment. The mCPs produced by two processes -- meson decay and proto
Externí odkaz:
http://arxiv.org/abs/2412.04854
Background: Positron emission tomography (PET) is widely used for studying dynamic processes, such as myocardial perfusion, by acquiring data over time frames. Kinetic modeling in PET allows for the estimation of physiological parameters, offering in
Externí odkaz:
http://arxiv.org/abs/2412.04706
Autor:
Tamagawa, Toru, Enoto, Teruaki, Kitaguchi, Takao, Iwakiri, Wataru, Kato, Yo, Numazawa, Masaki, Mihara, Tatehiro, Takeda, Tomoshi, Ota, Naoyuki, Watanabe, Sota, Aoyama, Amira, Iwata, Satoko, Takahashi, Takuya, Yamasaki, Kaede, Hu, Chin-Ping, Takahashi, Hiromitsu, Yoshida, Yuto, Sato, Hiroki, Hayashi, Shoki, Zhou, Yuanhui, Uchiyama, Keisuke, Jujo, Arata, Odaka, Hirokazu, Tamba, Tsubasa, Taniguchi, Kentaro
NinjaSat is an X-ray CubeSat designed for agile, long-term continuous observations of bright X-ray sources, with the size of 6U ($100\times200\times300$ mm$^3$) and a mass of 8 kg. NinjaSat is capable of pointing at X-ray sources with an accuracy of
Externí odkaz:
http://arxiv.org/abs/2412.03016
Autor:
Lin, Hexiang, Zhu, Huihui, Tang, Zan, Luo, Wei, Wang, Wei, Mak, Man-Wai, Jiang, Xudong, Chin, Lip Ket, Kwek, Leong Chuan, Liu, Ai Qun
Quantum computing holds promise across various fields, particularly with the advent of Noisy Intermediate-Scale Quantum (NISQ) devices, which can outperform classical supercomputers in specific tasks. However, challenges such as noise and limited qub
Externí odkaz:
http://arxiv.org/abs/2412.02955
Recent advancements in large vision-language models (LVLM) have significantly enhanced their ability to comprehend visual inputs alongside natural language. However, a major challenge in their real-world application is hallucination, where LVLMs gene
Externí odkaz:
http://arxiv.org/abs/2412.02946