检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Akutsu, T. Ando, M. Arai, K. Arai, Y. Araki, S. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Bae, Y. Baiotti, L. Bajpai, R. Barton, M.A. Cannon, K. Cao, Z. Capocasa, E. Chan, M. Chen, C. Chen, K. Chen, Y. Chiang, C.-I. Chu, H. Chu, Y.-K. Eguchi, S. Enomoto, Y. Flaminio, R. Fujii, Y. Fujikawa, Y. Fukunaga, M. Fukushima, M. Furuhata, T. Gao, D. Ge, G.-G. Ha, S. Hagiwara, A. Haino, S. Han, W.-B. Hasegawa, K. Hattori, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hiranuma, Y. Hirata, N. Hirose, E. Hong, Z. Hsieh, B.-H. Huang, G.-Z. Huang, H.-Y. Huang, P. Huang, Y.-C. Huang, Y.-J. Hui, D.C.Y. Ide, S. Ikenoue, B. Imam, S. Inayoshi, K. Inoue, Y. Ioka, K. Ito, K. Itoh, Y. Izumi, K. Jeon, C. Jin, H.-B. Jung, K. Jung, P. Kaihotsu, K. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanbara, S. Kanda, N. Kang, G. Kataoka, Y. Kawaguchi, K. Kawai, N. Kawasaki, T. Kim, C. Kim, J. Kim, J.C. Kim, W.S. Kim, Y.-M. Kimura, N. Kita, N. Kitazawa, H. Kojima, Y. Kokeyama, K. Komori, K. Kong, A.K.H. Kotake, K. Kozakai, C. Kozu, R. Kumar, R. Kume, J. Kuo, C. Kuo, H.-S. Kuromiya, Y. Kuroyanagi, S. Kusayanagi, K. Kwak, K. Lee, H.K. Lee, H.W. Lee, R. Leonardi, M. Li, K.L. Lin, L.C.-C. Lin, C.-Y. Lin, F.-K. Lin, F.-L. Lin, H.L. Liu, G.C. Luo, L.-W. Majorana, E. Marchio, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, A. Miyazaki, Y. Miyo, K. Miyoki, S. Mori, Y. Morisaki, S. Moriwaki, Y. Nagano, K. Nagano, S. Nakamura, K. Nakano, H. Nakano, M. Nakashima, R. Nakayama, Y. Narikawa, T. Naticchioni, L. Negishi, R. Nguyen Quynh, L. Ni, W.-T. Nishizawa, A. Nozaki, S. Obuchi, Y. Ogaki, W. Oh, J.J. Oh, K. Oh, S.H. Ohashi, M. Ohishi, N. Ohkawa, M. Ohta, H. Okutani, Y. Okutomi, K. Oohara, K. Ooi, C. Oshino, S. Otabe, S. Pan, K.-C. Pang, H. Parisi, A. Park, J. Pena Arellano, F.E. Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Research Center for the Early Universe The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba277-8582 Japan 1-1 Oho Tsukuba City Ibaraki305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo113-0032 Japan Department of Mathematics and Physics Graduate School of Science and Technology Hirosaki University 3 Bunkyo-cho Aomori Hirosaki036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Gifu Hida City506-1205 Japan 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan Korea Institute of Science and Technology Information 245 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon34047 Korea Republic of International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka560-0043 Japan 1-1 Oho Tsukuba City Ibaraki305-0801 Japan Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka Fukuoka City814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Rd. Danshui Dist. New Taipei City25137 Taiwan Department of Physics Institute of Astronomy National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University No.300 Zhongda

KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25th to March 10th, 2020, and its first joint observation with the GEO 600 detector from April 7th - 21st, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kHz, whereas the laser intensity did not significantly limit the detector sensitivity. © 2022, CC BY.

关键词： Gravity waves

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Cloud-based approximate constrained shortest distance queries over encrypted graphs with privacy protection

arXiv

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arXiv 2018年

作者： Shen, Meng Ma, Baoli Zhu, Liehuang Mijumbi, Rashid Du, Xiaojiang Hu, Jiankun Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications School of Computer Science Beijing Institute of Technology Beijing China Bell Labs CTO Nokia Dublin Ireland Department of Computer and Information Sciences Temple University Philadelphia United States Canberra Australia

Constrained shortest distance (CSD) querying is one of the fundamental graph query primitives, which finds the shortest distance from an origin to a destination in a graph with a constraint that the total cost does not exceed a given threshold. CSD querying has a wide range of applications, such as routing in telecommunications and transportation. With an increasing prevalence of cloud computing paradigm, graph owners desire to outsource their graphs to cloud servers. In order to protect sensitive information, these graphs are usually encrypted before being outsourced to the cloud. This, however, imposes a great challenge to CSD querying over encrypted graphs. Since performing constraint filtering is an intractable task, existing work mainly focuses on unconstrained shortest distance queries. CSD querying over encrypted graphs remains an open research problem. In this paper, we propose Connor, a novel graph encryption scheme that enables approximate CSD querying. Connor is built based on an efficient, tree-based ciphertext comparison protocol, and makes use of symmetric-key primitives and the somewhat homomorphic encryption, making it computationally efficient. Using Connor, a graph owner can first encrypt privacy-sensitive graphs and then outsource them to the cloud server, achieving the necessary privacy without losing the ability of querying. Extensive experiments with real-world datasets demonstrate the effectiveness and efficiency of the proposed graph encryption scheme. Copyright © 2018, The Authors. All rights reserved.

关键词： Graphic methods

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

arXiv

引用

arXiv 2022年

作者： Abe, H. Akutsu, T. Ando, M. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Bae, Y. Bajpai, R. Cannon, K. Cao, Z. Capocasa, E. Chan, M. Chen, C. Chen, D. Chen, K. Chen, Y. Chiang, C.-Y. Chu, Y.-K. Eguchi, S. Eisenmann, M. Enomoto, Y. Flaminio, R. Fong, H.K. Fujii, Y. Fujikawa, Y. Fujimoto, Y. Fukunaga, I. Gao, D. Ge, G.-G. Ha, S. Hadiputrawan, I.P.W. Haino, S. Han, W.-B. Hasegawa, K. Hattori, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hirata, N. Hirose, C. Ho, T.-C. Hsieh, B.-H. Hsieh, H.-F. Hsiung, C. Huang, H.-Y. Huang, P. Huang, Y.-C. Huang, Y.-J. Hui, D.C.Y. Ide, S. Inayoshi, K. Inoue, Y. Ito, K. Itoh, Y. Jeon, C. Jin, H.-B. Jung, K. Jung, P. Kaihotsu, K. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanda, N. Kato, T. Kawaguchi, K. Kim, C. Kim, J. Kim, J.C. Kim, Y.-M. Kimura, N. Kiyota, T. Kobayashi, Y. Kohri, K. Kokeyama, K. Kong, A.K.H. Koyama, N. Kozakai, C. Kume, J. Kuromiya, Y. Kuroyanagi, S. Kwak, K. Lee, E. Lee, H.W. Lee, R. Leonardi, M. Li, K.L. Li, P. Lin, L.C.-C. Lin, C.-Y. Lin, E.T. Lin, F.-K. Lin, F.-L. Lin, H.L. Liu, G.C. Luo, L.-W. Ma'arif, M. Majorana, E. Michimura, Y. Mio, N. Miyakawa, O. Miyo, K. Miyoki, S. Mori, Y. Morisaki, S. Morisue, N. Moriwaki, Y. Nagano, K. Nakamura, K. Nakano, H. Nakano, M. Nakayama, Y. Narikawa, T. Naticchioni, L. Nguyen Quynh, L. Ni, W.-T. Nishimoto, T. Nishizawa, A. Nozaki, S. Obayashi, Y. Ogaki, W. Oh, J.J. Oh, K. Ohashi, M. Ohashi, T. Ohkawa, M. Ohta, H. Okutani, Y. Oohara, K. Oshino, S. Otabe, S. Pan, K.-C. Parisi, A. Park, J. Peña Arellano, F.E. Saha, S. Saito, Y. Sakai, K. Sawada, T. Sekiguchi, Y. Shao, L. Shikano, Y. Shimizu, H. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Song, I. Sugimoto, R. Suresh, J. Suzuki, T. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takano, S. Takeda, H. Takeda, M. Tanaka, K. Tanaka, T. Tanaka, T. Tanioka, S. Taruya, A. Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo152-8551 Japan Mitaka City Tokyo181-8588 Japan Mitaka City Tokyo181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo113-0033 Japan The University of Tokyo Bunkyo-ku Tokyo113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Aomori Hirosaki City036-8561 Japan Kamioka-cho Hida City Gifu506-1205 Japan Mitaka City Tokyo181-8588 Japan Yuseong-gu Daejeon34141 Korea Republic of National Institute for Mathematical Sciences Yuseong-gu Daejeon34047 Korea Republic of Ibaraki Tsukuba City305-0801 Japan Department of Astronomy Beijing Normal University Beijing100875 China Department of Applied Physics Fukuoka University Jonan Fukuoka Fukuoka City814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City25137 Taiwan Department of Physics Institute of Astronomy National Tsing Hua University Hsinchu30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City32001 Taiwan Department of Physics National Tsing Hua University Hsinchu30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei11529 Taiwan Université Savoie Mont Blanc CNRS IN2P3 AnnecyF-74941 France Department of Astronomy The University of Tokyo Mitaka City Tokyo181-8588 Japan Faculty of Engineering Niigata University Nishi-ku Niigata Niigata City950-2181 Japan Department of Physics Graduate School of Science Osaka City University Sumiyoshi-ku Osaka City Osaka558-8585 Japan Chinese Academy of Sciences Xiao Hong Shan Wuhan430071 China Ulju-gun Ulsan44919 Korea Republic of Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China KAGRA Observatory The University of Tok

In April 2020, KAGRA conducted its first science observation in combination with the GEO 600 detector (O3GK) for two weeks. According to the noise budget estimation, suspension control noise in the low frequency band and acoustic noise in the middle frequency band are identified as the dominant contribution. In this study, we show that such noise can be reduced in offline data analysis by utilizing a method called Independent Component Analysis (ICA). Here the ICA model is extended from the one studied in iKAGRA data analysis by incorporating frequency dependence while linearity and stationarity of the couplings are still assumed. By using optimal witness sensors, those two dominant contributions are mitigated in the real observational data. We also analyze the stability of the transfer functions for whole two weeks data in order to investigate how the current subtraction method can be practically used in gravitational wave search. Copyright © 2022, The Authors. All rights reserved.

关键词： Data handling

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From qestion to text: Qestion-oriented feature atention for answer selection

引用

ACM Transactions on Information Systems 2018年第1期37卷

作者： Huang, Heyan Wei, Xiaochi Nie, Liqiang Mao, Xianling Xu, Xin-Shun Beijing Eng. Res. Ctr. of High Vol. Language Information Processing and Cloud Computing Applications School of Computer Beijing Institute of Technology No.5 Zhongguancun South Street Haidian Beijing100081 China School of Computer Science Shandong University 72 Binhai Road Jimo Qingdao Shandong Province266237 China

Understanding unstructured texts is an essential skill for human beings as it enables knowledge acquisition. Although understanding unstructured texts is easy for we human beings with good education, it is a great challenge for machines. Recently, with the rapid development of artifcial intelligence techniques, researchers put efforts to teach machines to understand texts and justify the educated machines by letting them solve the questions upon the given unstructured texts, inspired by the reading comprehension test as we humans do. However, feature effectiveness with respect to different questions signifcantly hinders the performance of answer selection, because different questions may focus on various aspects of the given text and answer candidates. To solve this problem, we propose a question-oriented feature attention (QFA) mechanism, which learns to weight different engineering features according to the given question, so that important features with respect to the specifc question is emphasized accordingly. Experiments on MCTest dataset have wellvalidated the effectiveness of the proposed method. Additionally, the proposed QFA is applicable to various IR tasks, such as question answering and answer selection. We have verifed the applicability on a crawled community-based question-answering dataset. © 2018 ACM.

关键词： Feature extraction

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Improving Galaxy Cluster Selection with the Outskirt Stellar Mass of Galaxies

arXiv

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arXiv 2024年

作者： Kwiecien, Matthew Jeltema, Tesla Leauthaud, Alexie Huang, Song Rykoff, Eli Heydenreich, Sven Lange, Johannes Everett, Spencer Zhou, Conghao Kelly, Paige Zhang, Yuanyuan Shin, Tae-Hyeon Golden-Marx, Jesse Marshall, J.L. Aguena, M. Allam, S.S. Bocquet, S. Brooks, D. Rosell, A. Carnero Carretero, J. da Costa, L.N. Pereira, M.E.S. Davis, T.M. De Vicente, J. Doel, P. Ferrero, I. Flaugher, B. Frieman, J. García-Bellido, J. Gatti, M. Gaztanaga, E. Giannini, G. Gruen, D. Gruendl, R.A. Gutierrez, G. Hinton, S.R. Hollowood, D.L. Honscheid, K. James, D.J. Lee, S. Miquel, R. Pieres, A. Malagón, A.A. Plazas Romer, A.K. Samuroff, S. Sanchez, E. Santiago, B. Sevilla-Noarbe, I. Smith, M. Suchyta, E. Swanson, M.E.C. Tarle, G. Tucker, D.L. Vikram, V. Weaverdyck, N. Wiseman, P. Department of Physics University of California Santa CruzCA95064 United States Santa Cruz Institute for Particle Physics University of California Santa CruzCA95064 United States Department of Astrophysics University of California Santa CruzCA95064 United States Department of Astronomy Tsinghua University Beijing100084 China Kavli Institute for Particle Astrophysics and Cosmology Stanford University P. O. Box 2450 StanfordCA94305 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Department of Physics University of Michigan Ann ArborMI48109 United States Leinweber Center for Theoretical Physics University of Michigan Ann ArborMI48109 United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Department of Physics and Astronomy University of California Davis DavisCA95616 United States NSF’s National Optical-Infrared Astronomy Research Laboratory 950 Cherry Ave. TucsonAZ85719 United States Department of Physics and Astronomy Stony Brook University Stony BrookNY United States School of Physics and Astronomy University of Nottingham NottinghamNG7 2RD United Kingdom George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy Department of Physics and Astronomy Texas A&M University College StationTX77843 United States Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States University Observatory Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich81679 Germany Department of Physics & Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Instituto de Astrofisica de Canarias Tenerife La LagunaE-38205 Spain Universidad de La Laguna Dpto. Astrofísica Tenerife La LagunaE-38206 Spain The Barcelona Institute of Science and Technology Campus UAB

The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, S8. However, recent results have shown that clusters chosen by the redMaPPer algorithm show richness-dependent biases that affect the weak lensing signals and number densities of clusters, increasing uncertainty in the cluster mass calibration and reducing their constraining power. In this work, we evaluate an alternative cluster proxy, outskirt stellar mass, Mout, defined as the total stellar mass within a [50, 100] kpc envelope centered on a massive galaxy. This proxy exhibits scatter comparable to redMaPPer richness, λ, but is less likely to be subject to projection effects. We compare the Dark Energy Survey Year 3 redMaPPer cluster catalog with a Mout selected cluster sample from the Hyper-Suprime Camera survey. We use weak lensing measurements to quantify and compare the scatter of Mout and λ with halo mass. Our results show Mout has a scatter consistent with λ, with a similar halo mass dependence, and that both proxies contain unique information about the underlying halo mass. We find λ-selected samples introduce features into the measured ∆Σ signal that are not well fit by a log-normal scatter only model, absent in Mout selected samples. Our findings suggest that Mout offers an alternative for cluster selection with more easily calibrated selection biases, at least at the generally lower richnesses probed here. Combining both proxies may yield a mass proxy with a lower scatter and more tractable selection biases, enabling the use of lower mass clusters in cosmology. Finally, we find the scatter and slope in the λ − Mout scaling relation to be 0.49 ± 0.02 and 0.38 ± 0.09. © 2024, CC BY.

关键词： Galaxies

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The status of KAGRA underground cryogenic gravitational wave telescope 15

The status of KAGRA underground cryogenic gravitational wave...

引用

15th International Conference on Topics in Astroparticle and Underground Physics, TAUP 2017

作者： Akutsu, T. Ando, M. Araya, A. Aritomi, N. Asada, H. Aso, Y. Atsuta, S. Awai, K. Barton, M.A. Cannon, K. Craig, K. Creus, W. Doi, K. Eda, K. Enomoto, Y. Flaminio, R. Fujii, Y. Fujimoto, M.-K. Furuhata, T. Haino, S. Hasegawa, K. Hashino, K. Hayama, K. Hirobayashi, S. Hirose, E. Hsieh, A.H. Inoue, Y. Ioka, K. Itoh, Y. Kaji, T. Kajita, T. Kakizaki, M. Kamiizumi, M. Kambara, S. Kanda, N. Kanemura, S. Kaneyama, M. Kang, G. Kasuya, J. Kataoka, Y. Kawai, N. Kawamura, S. Kim, C. Kim, H. Kim, J. Kim, Y. Kimura, N. Kinugawa, T. Kirii, S. Kitaoka, Y. Kojima, Y. Kokeyama, K. Komori, K. Kotake, K. Kumar, R. Lee, H. Lee, H. Liu, Y. Luca, N. Majorana, E. Mano, S. Marchio, M. Matsui, T. Matsushima, F. Michimura, Y. Miyakawa, O. Miyamoto, T. Miyamoto, A. Miyo, K. Miyoki, S. Morii, W. Morisaki, S. Moriwaki, Y. Morozumi, T. Musha, M. Nagano, S. Nagano, K. Nakamura, K. Nakamura, T. Nakano, H. Nakano, M. Nakao, K. Narikawa, T. Quynh, L.Nguyen Ni, W.-T. Ochi, T. Oh, J. Oh, S. Ohashi, M. Ohishi, N. Ohkawa, M. Okutomi, K. Oohara, K. Alleano, F.E.P. Pinto, I. Sago, N. Saijo, M. Saito, Y. Sakai, K. Sakai, Y. Sasaki, Y. Sasaki, M. Sato, S. Sato, T. Sekiguchi, Y. Seto, N. Shibata, M. Shimoda, T. Shinkai, H. Shoda, A. Somiya, K. Son, E. Suemasa, A. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takeda, H. Tanaka, H. Tanaka, K. Tanaka, T. Tatsumi, D. Tomaru, T. Tomura, T. Travasso, F. Tsubono, K. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueki, S. Ueno, K. Ushiba, T. Van Putten, M.H.P.M. Vocca, H. Wada, S. Wakamatsu, T. Yamada, T. Yamamoto, S. Yamamoto, T. Yamamoto, K. Yamamoto, A. Yokoyama, J. Yokozawa, T. Yoon, T.H. Yuzurihara, H. Zeidler, S. Zhu, Z.-H. National Astronomical Observatory of Japan Mitaka Tokyo181-8588 Japan Department of Physics University of Tokyo Bunkyo Tokyo113-0033 Japan Earthquake Research Institute University of Tokyo Bunkyo Tokyo113-0032 Japan Department of Advanced Physics Hirosaki University Aomori Hirosaki036-8561 Japan National Astronomical Observatory of Japan Hida Gifu506-1205 Japan Department of Physics Tokyo Institute of Technology Meguro Tokyo152-8551 Japan Institute for Cosmic Ray Research University of Tokyo Hida Gifu506-1205 Japan Research Center for the Early Universe University of Tokyo Bunkyo Tokyo113-0033 Japan Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan Institute of Physics Academia Sinica Nankang Taipei11529 Taiwan Department of Physics University of Toyama Toyama Toyama930-8555 Japan Faculty of Engineering University of Toyama Toyama Toyama930-8555 Japan Yukawa Institute for Theoretical Physics Kyoto University Sakyo Kyoto606-8502 Japan Department of Physics Osaka City University Sumiyosi Osaka558-8585 Japan Department of Physics Osaka University Osaka Toyonaka560-0043 Japan Korea Institute of Science and Technology Information Yuseong Daejeon 34141 Korea Republic of Yuseong Daejeon34055 Korea Republic of National Institute for Mathematical Sciences Daejeon34047 Korea Republic of Department of Computer Simulation Inje University Gimhae Gyeongsangnam50834 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul151-742 Korea Republic of High Energy Accelerator Research Organization Ibaraki Tsukuba305-0801 Japan Department of Physical Science Hiroshima University Higashihiroshima Hiroshima903-0213 Japan Department of Applied Physics Fukuoka University Jonan Fukuoka814-0180 Japan Department of Advanced Materials Science University of Tokyo Chiba Kashiwa277-8582 Japan Istituto Nazionale di Fisica Nucleare Sapienza University Roma00185 Italy Department o

KAGRA is a 3-km interferometric gravitational wave telescope located in the Kamioka mine in Japan. It is the first km-class gravitational wave telescope constructed underground to reduce seismic noise, and the first km-class telescope to use cryogenic cooling of test masses to reduce thermal noise. The construction of the infrastructure to house the interferometer in the tunnel, and the initial phase operation of the interferometer with a simple 3-km Michelson configuration have been completed. The first cryogenic operation is expected in 2018, and the observing runs with a full interferometer are expected in 2020s. The basic interferometer configuration and the current status of KAGRA are described. © Published under licence by IOP Publishing Ltd.

关键词： Interferometers

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Hierarchical attention network for visually-aware food recommendation

arXiv

引用

arXiv 2018年

作者： Gao, Xiaoyan Feng, Fuli He, Xiangnan Huang, Heyan Guan, Xinyu Feng, Chong Ming, Zhaoyan Chua, Tat-Seng Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications School of Computer Beijing Institute of Technology Beijing100081 China School of Computing National University of Singapore Singapore117417 Singapore University of Science and Technology of China Hefei Anhui230031 China Systems Engineering Institute Xi'an Jiaotong University Xi'an710049 China

Food recommender systems play an important role in assisting users to identify the desired food to eat. Deciding what food to eat is a complex and multi-faceted process, which is influenced by many factors such as the ingredients, appearance of the recipe, the user's personal preference on food, and various contexts like what had been eaten in the past meals. In this work, we formulate the food recommendation problem as predicting user preference on recipes based on three key factors that determine a user's choice on food, namely, 1) the user's (and other users') history;2) the ingredients of a recipe;and 3) the descriptive image of a recipe. To address this challenging problem, we develop a dedicated neural network-based solution Hierarchical Attention based Food Recommendation (HAFR) which is capable of: 1) capturing the collaborative filtering effect like what similar users tend to eat;2) inferring a user's preference at the ingredient level;and 3) learning user preference from the recipe's visual images. To evaluate our proposed method, we construct a large-scale dataset consisting of millions of ratings from ***. Extensive experiments show that our method outperforms several competing recommender solutions like Factorization Machine and Visual Bayesian Personalized Ranking with an average improvement of 12%, offering promising results in predicting user preference on food. Codes and dataset will be released upon acceptance. Copyright © 2018, The Authors. All rights reserved.

关键词： Recommender systems

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Attosecond Time Delay of Retrapped Resonant Ionization

引用

Physical Review Letters 2018年第10期121卷 103201-103201页

作者： Xiaohong Song Guangluo Shi Guojun Zhang Jingwen Xu Cheng Lin Jing Chen Weifeng Yang Department of Physics College of Science Shantou University Shantou Guangdong 515063 China Key Laboratory of High Energy Density Physics Simulation Center for Applied Physics and Technology Peking University Beijing 100084 China Institute of Applied Physics and Computational Mathematics P.O. Box 8009 Beijing 100088 China Collaborative Innovation Center of Inertial Fusion Sciences and Applications Shanghai Jiao Tong University Shanghai 200240 China

A recent ultrafast pump-probe technique has allowed measurement of time delays during photoemission in a variety of systems ranging from atoms and molecules to solids with unprecedented temporal resolution. However, identifying the underlying physics is still a challenge especially in complicated multichannel above-threshold ionization (ATI) experiments. Here we demonstrate that the time delays of different ionization pathways in ATI can be clearly resolved and extracted with a semiclassical statistical method. The remarkable phase shift of near threshold photoelectrons can be attributed to a temporary retrapping of a photoelectron by the atomic potential in a quasibound state after emerging in the continuum state. This continuum-bound-continuum scattering manifests as a new resonant effect in strong-field photoemission. Our results unify the seemingly opposing quantum Eisenbud-Wigner-Smith time delay and classical Coulomb-induced time delay by highlighting the same physical picture, which holds promise for an intuitive interpretation of time-resolved fundamental electronic processes in strong-field experiments and epistemological reexamination of the quantum-classical correspondence.

关键词： Electronic excitation & ionization Multiphoton or tunneling ionization & excitation Photoemission

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Noisy smoothing image source identification 1

引用

9th International Symposium on Cyberspace Safety and Security, CSS 2017

作者： Liu, Yuying Huang, Yonggang Zhang, Jun Liu, Xu Shen, Hualei School of Computer Science and Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology Beijing100081 China School of Information Technology Deakin University MelbourneVIC3125 Australia College of Computer and Information Engineering Henan Normal University Xinxiang453007 China

ISBN: (数字)9783319694719

ISBN: (纸本)9783319694702

Feature based image source identification plays an important role in the toolbox for forensics investigations on images. Conventional feature based identification schemes suffer from the problem of noise, that is, the training dataset contains noisy samples. To address this problem, we propose a new Noisy Smoothing Image Source Identification (NS-ISI) method. NS-ISI address the noise problem in two steps. In step 1, we employ a classifier ensemble approach for noise level evaluation for each training sample. The noise level indicates the probability of being noisy. In step 2, a noise sensitive sampling method is employed to sample training samples from original training set according to the noise level, producing a new training dataset. The experiments carried out on the Dresden image collection confirms the effectiveness of the proposed NS-ISI. When the noisy samples present, the identification accuracy of NS-ISI is significantly better than traditional methods. © 2017, Springer International Publishing AG.

关键词： Sampling

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A Hybrid Method of Domain Lexicon Construction for Opinion Targets Extraction Using Syntax and Semantics

引用

Journal of computer Science & technology 2016年第3期31卷 595-603页

作者： Chun Liao Chong Feng Sen Yang He-Yan Huang Department of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology Beijing 100081 China

Opinion targets extraction of Chinese microblogs plays an important role in opinion mining. There has been a significant progress in this area recently, especially the method based on conditional random field （CRF）. However, this method only takes lexicon-related features into consideration and does not excavate the implied syntactic and semantic knowledge. We propose a novel approach which incorporates domain lexicon with groups of syntactical and semantic features. The approach acquires domain lexicon through a novel way which explores syntactic and semantic information through Part- of-Speech, dependency structure, phrase structure, semantic role and semantic similarity based on word embedding. And then we combine the domain lexicon with opinion targets extracted from CRF with groups of features for opinion targets extraction. Experimental results on COAE2014 dataset show the outperformance of the approach compared with other well-known methods on the task of opinion targets extraction.

关键词： domain lexicon opinion targets extraction syntactic structure semantic role word embedding

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