检索结果-内蒙古大学图书馆

arXiv 2019年

作者： Liao, Hao Wu, Xingtong Zhou, Mingyang Yeung, Chi Ho National Engineering Laboratory for big data computing systems Guangdong Province Key Laboratory of Popular High Performance Computers College of Computer Science and Software Engineering Shenzhen University Department of Science and Environmental Studies Education University of Hong Kong Hong Kong

Many major cities suffer from severe traffic congestion. Road expansion in the cites is usually infeasible, and an alternative way to alleviate traffic congestion is to coordinate the route of vehicles. Various path selection and planning algorithms are thus proposed, but most existing methods only plan paths separately and provide un-coordinated solutions. Recently, an analogy between the coordination of vehicular routes and the interaction of polymers is drawn;the spin glass theory in statistical physics is employed to optimally coordinate transportation routes. To further examine the advantages brought by path coordination, we incorporate the link congestion function developed by the Bureau of Public Roads (BPR) into the polymer routing algorithm. We then estimate in simulations the traveling time of all users saved by the polymer-BPR algorithm in randomly generated networks and real transportation networks in major cities including London, New York and Beijing. We found that a large amount of traveling time is saved in all studied networks, suggesting that the approach inspired by polymer physics is effective in minimizing the traveling time via path coordination, which is a promising tool for alleviating traffic congestions. Copyright © 2019, The Authors. All rights reserved.

关键词： Statistical mechanics

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Multi-Source Data Integration-Based Urban Road GPS Environment Friendliness Estimation

Multi-Source Data Integration-Based Urban Road GPS Environme...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Liantao Ma Yasha Wang Guangju Peng Chaohe Zhang Chao Chen Junfeng Zhao Jiangtao Wang Key Laboratory of High Condence Software Technologies Ministry of Education Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China National Engineering Research Center of Software Engineering Peking University Beijing China College of Computer Science Chongqing University China School of Computing and Communications Lancaster University UK

ISBN: (数字)9781728140346

ISBN: (纸本)9781728140353

In urban areas, multipath errors may occur due to blockage and reflection of GPS signals by buildings, and significantly reduce the accuracy of GPS positioning. The degree to which the environment causes multipath errors and negatively impacts GPS accuracy is referred to as GPS Environment Friendliness (GEF) in this paper. The estimation of GEF helps location-based-service remind users to reduce the psychological expectation of GPS accuracy when they enter a poor GEF area. While existing studies estimate the GEF only based on the vehicle trajectory data, we propose a more efficient matrix completion-based approach that uses the historical bus trajectory data with the integration of the building layout information and road tag information. Based on one month GPS trajectory data of 4835 buses within the second ring road in Chengdu, China, we estimate the GEF of 8831 different road segments and verify the rationality of the results by satellite maps, street views, and field tests.

关键词： Global Positioning System Roads Urban areas Trajectory Receivers Buildings Position measurement

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Enhancing countries' fitness with recommender systems on the international trade network

arXiv

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arXiv 2019年

作者： Liao, Hao Wu, Xing-Tong Vidmer, Alexandre Huang, Xiao-Min Liu, Ming-Kai Zhou, Mingyang Zhang, Yi-Cheng National Engineering Laboratory for Big Data System Computing Technology Guangdong Province Key Laboratory of Popular High Performance Computers College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Physics University of Fribourg Fribourg1700 Switzerland

Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries' data of the international trading network. A recommendation system is then used to identify the products corresponding to the production capacity of each individual country, but are somehow overlook by the country. Then, we simulate the evolution of the country's fitness if it would have followed the recommendations. The result of this work is the combination combine these two methods to provide insights to countries on how to enhance the diversification of their exported products in a scientific way and improve national competitiveness significantly, especially for developing countries. Copyright © 2019, The Authors. All rights reserved.

关键词： Recommender systems

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Foundation models and intelligent decision-making: Progress, challenges, and perspectives

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The Innovation 2025年第6期6卷

作者： Jincai Huang Yongjun Xu Qi Wang Qi (Cheems) Wang Xingxing Liang Fei Wang Zhao Zhang Wei Wei Boxuan Zhang Libo Huang Jingru Chang Liantao Ma Ting Ma Yuxuan Liang Jie Zhang Jian Guo Xuhui Jiang Xinxin Fan Zhulin An Tingting Li Aiguo Fei Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China National Engineering Research Center for Software Engineering Peking University Beijing 100871 China College of Systems Engineering National University of Defense Technology Changsha 410073 China Department of Oral Implantology Peking University School and Hospital of Stomatology Beijing 100081 China Laboratory for Big Data and Decision National University of Defense Technology Changsha 410073 China School of Automation Beijing Institute of Technology Beijing 100081 China Huazhong University of Science and Technology Wuhan 430074 China University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of AI Safety Beijing 100190 China Department of Automation Tsinghua University Beijing 100084 China School of Information Science and Engineering Dalian Polytechnic University Dalian 116034 China The Hong Kong University of Science and Technology (Guangzhou) Guangzhou 511453 China College of Information and Electrical Engineering China Agricultural University Beijing 100083 China State Key Laboratory of Efficient Utilization of Agricultural Water Resources Beijing 100083 China IDEA Research International Digital Economy Academy Shenzhen 518057 China School of Computer Science National Pilot Software Engineering School Beijing University of Posts and Telecommunications Beijing 100876 China

Intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and adaptive choices and decompose complex tasks into manageable steps, such as AI agents and high-level reinforcement learning. Recent advances in multimodal foundation-based approaches unify diverse input modalities—such as vision, language, and sensory data—into a cohesive decision-making process. Foundation models (FMs) have become pivotal in science and industry, transforming decision-making and research capabilities. Their large-scale, multimodal data-processing abilities foster adaptability and interdisciplinary breakthroughs across fields such as healthcare, life sciences, and education. This survey examines IDM’s evolution, advanced paradigms with FMs and their transformative impact on decision-making across diverse scientific and industrial domains, highlighting the challenges and opportunities in building efficient, adaptive, and ethical decision systems.

关键词： artificial intelligence intelligent decision-making foundation models agent large language model

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Empirical topological investigation of practical supply chains based on complex networks

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Chinese Physics B 2017年第11期26卷 144-150页

作者：廖好沈婧吴兴桐陈博奎周明洋 National Engineering Laboratory for Big Data Computing Systems Guangdong Province Key Laboratory of Popular High Performance ComputersCollege of Computer Science and Software Engineering Shenzhen University Department of Computer Science School of Computing National University of Singapore

The industrial supply chain networks basically capture the circulation of social resource, dominating the stability and efficiency of the industrial system. In this paper, we provide an empirical study of the topology of smartphone supply chain network. The supply chain network is constructed using open online data. Our experimental results show that the smartphone supply chain network has small-world feature with scale-free degree distribution, in which a few high degree nodes play a key role in the function and can effectively reduce the communication cost. We also detect the community structure to find the basic functional unit. It shows that information communication between nodes is crucial to improve the resource utilization. We should pay attention to the global resource configuration for such electronic production management.

关键词： China supply chain networks complex networks data science network science

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Development of Gravity Field Calibrator for KAGRA 38

Development of Gravity Field Calibrator for KAGRA

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38th International Cosmic Ray Conference, ICRC 2023

作者： Bajpai, Rishabh Abe, H. Akutsu, T. Ando, M. Aoumi, M. Araya, A. Aritomi, N. Aso, Y. Bae, S. Bajpai, R. Cannon, K. Cao, Z. Chang, R.-J. Chen, A.H.-Y. Chen, D. Chen, H. Chen, Y. Chiba, A. Chiba, R. Chou, C. Eisenmann, M. Fujii, S. Fukunaga, I. Haba, D. Haino, S. Han, W.-B. Hayakawa, H. Hayama, K. Himemoto, Y. Hirata, N. Hirose, C. Hoshino, S. Hsieh, H.-F. Hsiung, C. Hsu, S.-C. Hui, D.C.Y. Inayoshi, K. Itoh, Y. Iwaya, M. Jin, H.-B. Jung, K. Kajita, T. Kamiizumi, M. Kanda, N. Kato, J. Kato, T. Kim, S. Kimura, N. Kiyota, T. Kohri, K. Kokeyama, K. Komori, K. Kong, A.K.H. Koyama, N. Kume, J. Kuroyanagi, S. Kuwahara, S. Kwak, K. Lai, S. Lee, H.W. Lee, R. Lee, S. Leonardi, M. Li, K.L. Lin, L.C.-C. Lin, C.-Y. Lin, E.T. Liu, G.C. Ma, L.-T. Maeda, K. Matsuyama, M. Meyer-Conde, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, S. Miyoki, S. Morisaki, S. Moriwaki, Y. Murakoshi, M. Nakamura, K. Nakano, H. Narikawa, T. Nguyen Quynh, L. Nishino, Y. Nishizawa, A. Obayashi, K. Oh, J.J. Oh, K. Ohashi, M. Ohkawa, M. Oohara, K. Oshima, Y. Oshino, S. Page, M.A. Pan, K.-C. Park, J. Peña Arellano, F.E. Saha, S. Sakai, K. Sako, T. Sato, R. Sato, S. Sato, Y. Sawada, T. Sekiguchi, Y. Shao, L. Shikano, Y. Shimode, K. Shinkai, H. Shiota, J. Somiya, K. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takatani, K. Takeda, H. Takeda, M. Tamaki, M. Tanaka, K. Tanaka, S.J. Tanaka, T. Taruya, A. Tomaru, T. Tomita, K. Tomura, T. Toriyama, A. Trani, A.A. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueno, K. Ushiba, T. van Putten, M.H.P.M. Wang, H. Washimi, T. Wu, C. Wu, H. Yamamoto, K. Yamamoto, M. Yamamoto, T. Yamamoto, T.S. Yamamura, S. Yamazaki, R. Yang, L.-C. Yang, Y. Yeh, S.-W. Yokoyama, J. Yokozawa, T. Yuzurihara, H. Zhao, Y. Zhu, Z.-H. National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo Japan Graduate School of Science Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8551 Japan 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 The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo113-0032 Japan LIGO Hanford Observatory RichlandWA99352 United States 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan 245 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing100875 China Department of Physics National Cheng Kung University No.1 University Road Tainan City701 Taiwan Institute of Physics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Department of Physics National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu30013 Taiwan Faculty of Science University of Toyama 3190 Gofuku Toyama City Toyama930-8555 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa City277-8582 Japan Department of Electrophysics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Department of Physics Graduate School of Science Osaka Metropolitan University 3-3-138 Sugimoto-cho Sumiyoshi-ku Osaka City Osaka558-

The output of a gravitational wave telescope is a voltage signal which needs to be calibrated to get the strain signal h(t). This signal h(t) can then be used to derive various parameters of the gravitational wave sources. Any uncertainty in the calibration is directly transferred to these parameters. Therefore, absolute calibration of gravitation wave detectors using a precise reference (known) signal is essential. Currently, KAGRA uses Photon Calibrator (PCAL) to generate reference signals for calibration. PCAL injects a power-modulated laser onto the test mass to calibrate the absolute displacement of the mirror using radiation pressure. Hence, the absolute calibration of KAGRA is limited to 3% by the absolute laser power measurement uncertainty due to the deviation in the laser power standards. KAGRA proposed a new method combining PCAL with Gravity Field Calibrator (GCAL) to reduce the calibration uncertainty. GCAL modulates the test mass using a dynamic gravitational field generated by rotating multipole masses. Since the injected force by GCAL depends on the gravitational constant, mass, distance, rotation frequency, and radius, calibration uncertainty in the sub-percent region can be achieved. In this paper, we will report on the progress of the development of the gravity field calibrator and our future plans. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Laser mirrors

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Calibration of the gravitational wave telescope KAGRA 38

Calibration of the gravitational wave telescope KAGRA

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38th International Cosmic Ray Conference, ICRC 2023

作者： Chen, Dan Abe, H. Akutsu, T. Ando, M. Aoumi, M. Araya, A. Aritomi, N. Aso, Y. Bae, S. Bajpai, R. Cannon, K. Cao, Z. Chang, R.-J. Chen, A.H.-Y. Chen, D. Chen, H. Chen, Y. Chiba, A. Chiba, R. Chou, C. Eisenmann, M. Fujii, S. Fukunaga, I. Haba, D. Haino, S. Han, W.-B. Hayakawa, H. Hayama, K. Himemoto, Y. Hirata, N. Hirose, C. Hoshino, S. Hsieh, H.-F. Hsiung, C. Hsu, S.-C. Hui, D.C.Y. Inayoshi, K. Itoh, Y. Iwaya, M. Jin, H.B. Jung, K. Kajita, T. Kamiizumi, M. Kanda, N. Kato, J. Kato, T. Kim, S. Kimura, N. Kiyota, T. Kohri, K. Kokeyama, K. Komori, K. Kong, A.K.H. Koyama, N. Kume, J. Kuroyanagi, S. Kuwahara, S. Kwak, K. Lai, S. Lee, H.W. Lee, R. Lee, S. Leonardi, M. Li, K.L. Lin, L.C.-C. Lin, C.-Y. Lin, E.T. Liu, G.C. Ma, L.-T. Maeda, K. Matsuyama, M. Meyer-Conde, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, S. Miyoki, S. Morisaki, S. Moriwaki, Y. Murakoshi, M. Nakamura, K. Nakano, H. Narikawa, T. Nguyen Quynh, L. Nishino, Y. Nishizawa, A. Obayashi, K. Oh, J.J. Oh, K. Ohashi, M. Ohkawa, M. Oohara, K. Oshima, Y. Oshino, S. Page, M.A. Pan, K.-C. Park, J. Peña Arellano, F.E. Saha, S. Sakai, K. Sako, T. Sato, R. Sato, S. Sato, Y. Sawada, T. Sekiguchi, Y. Shao, L. Shikano, Y. Shimode, K. Shinkai, H. Shiota, J. Somiya, K. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takatani, K. Takeda, H. Takeda, M. Tamaki, M. Tanaka, K. Tanaka, S.J. Tanaka, T. Taruya, A. Tomaru, T. Tomita, K. Tomura, T. Toriyama, A. Trani, A.A. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueno, K. Ushiba, T. van Putten, M.H.P.M. Wang, H. Washimi, T. Wu, C. Wu, H. Yamamoto, K. Yamamoto, M. Yamamoto, T. Yamamoto, T.S. Yamamura, S. Yamazaki, R. Yang, L.-C. Yang, Y. Yeh, S.-W. Yokoyama, J. Yokozawa, T. Yuzurihara, H. Zhao, Y. Zhu, Z.-H. Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Graduate School of Science Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8551 Japan 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 The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo113-0032 Japan LIGO Hanford Observatory RichlandWA99352 United States 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan 245 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing100875 China Department of Physics National Cheng Kung University No.1 University Road Tainan City701 Taiwan Institute of Physics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Department of Physics National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu30013 Taiwan Faculty of Science University of Toyama 3190 Gofuku Toyama City Toyama930-8555 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa City277-8582 Japan Department of Electrophysics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Department of Physics Graduate School of Science Osaka Metropolitan University 3-3-138 Sugimoto-cho Sumiyoshi-ku Osaka City Osaka558-8585 Japan Institute of Physics Academia Sinica 128 Sec. 2 Academia Rd. Na

KAGRA is a laser interferometric gravitational wave (GW) telescope in Japan. It joined O4, the fourth international GW observation run, with other telescopes, namely, Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo. In the previous GW observation runs: O1, O2, and O3, 90 events were reported, and many more events are expected to be observed in O4. With the beginning of GW astronomy, the calibration of observed GW signals is becoming more important than ever before. The main calibration system used in KAGRA, LIGO, and Virgo is a photon calibration system (Pcal), which injects reference signals into a telescope by the radiation pressure of a laser. On the basis of the preparation and operation of KAGRA Pcals in O3, we prepared an upgrading plan for O4. This plan includes three main improvements: improving the Pcal laser beam alignment system, reducing noise, and dereasing uncertainty. Improvement works were conducted between the end of O3 and the start of O4 in accordance with this plan. The following results were obtained: first, precise remote alignment was enabled in the critical Pcal laser path region. Second, a Pcal noise source was identified and noise was significantly improved, resulting in a remarkable 50 dB reduction and sufficient reduction of the Pcal noise below the design sensitivity of KAGRA. Third, studies on the temperature dependence and laser incidence state dependence of the integrating sphere-type power meter were conducted to reduce the uncertainty of the Pcal, which is directly related to the uncertainty of the telescope signal. The details of the KAGRA Pcal and the improvements made between O3 and O4 are reported in this study. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Laser interferometry

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Status of KAGRA 38

Status of KAGRA

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38th International Cosmic Ray Conference, ICRC 2023

作者： Itoh, Yousuke Abe, H. Akutsu, T. Ando, M. Aoumi, M. Araya, A. Aritomi, N. Aso, Y. Bae, S. Bajpai, R. Cannon, K. Cao, Z. Chang, R.-J. Chen, A.H.-Y. Chen, D. Chen, H. Chen, Y. Chiba, A. Chiba, R. Chou, C. Eisenmann, M. Fujii, S. Fukunaga, I. Haba, D. Haino, S. Han, W.-B. Hayakawa, H. Hayama, K. Himemoto, Y. Hirata, N. Hirose, C. Hoshino, S. Hsieh, H.-F. Hsiung, C. Hsu, S.-C. Hui, D.C.Y. Inayoshi, K. Itoh, Y. Iwaya, M. Jin, H.B. Jung, K. Kajita, T. Kamiizumi, M. Kanda, N. Kato, J. Kato, T. Kim, S. Kimura, N. Kiyota, T. Kohri, K. Kokeyama, K. Komori, K. Kong, A.K.H. Koyama, N. Kume, J. Kuroyanagi, S. Kuwahara, S. Kwak, K. Lai, S. Lee, H.W. Lee, R. Lee, S. Leonardi, M. Li, K.L. Lin, L.C.-C. Lin, C.-Y. Lin, E.T. Liu, G.C. Ma, L.-T. Maeda, K. Matsuyama, M. Meyer-Conde, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, S. Miyoki, S. Morisaki, S. Moriwaki, Y. Murakoshi, M. Nakamura, K. Nakano, H. Narikawa, T. Nguyen Quynh, L. Nishino, Y. Nishizawa, A. Obayashi, K. Oh, J.J. Oh, K. Ohashi, M. Ohkawa, M. Oohara, K. Oshima, Y. Oshino, S. Page, M.A. Pan, K.-C. Park, J. Peña Arellano, F.E. Saha, S. Sakai, K. Sako, T. Sato, R. Sato, S. Sato, Y. Sawada, T. Sekiguchi, Y. Shao, L. Shikano, Y. Shimode, K. Shinkai, H. Shiota, J. Somiya, K. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takatani, K. Takeda, H. Takeda, M. Tamaki, M. Tanaka, K. Tanaka, S.J. Tanaka, T. Taruya, A. Tomaru, T. Tomita, K. Tomura, T. Toriyama, A. Trani, A.A. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueno, K. Ushiba, T. van Putten, M.H.P.M. Wang, H. Washimi, T. Wu, C. Wu, H. Yamamoto, K. Yamamoto, M. Yamamoto, T. Yamamoto, T.S. Yamamura, S. Yamazaki, R. Yang, L.-C. Yang, Y. Yeh, S.-W. Yokoyama, J. Yokozawa, T. Yuzurihara, H. Zhao, Y. Zhu, Z.-H. Osaka Metropolitan University Sumiyoshi Osaka3-3-138 Japan Graduate School of Science Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8551 Japan 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 The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo113-0032 Japan LIGO Hanford Observatory RichlandWA99352 United States 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan 245 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing100875 China Department of Physics National Cheng Kung University No.1 University Road Tainan City701 Taiwan Institute of Physics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Department of Physics National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu30013 Taiwan Faculty of Science University of Toyama 3190 Gofuku Toyama City Toyama930-8555 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa City277-8582 Japan Department of Electrophysics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Department of Physics Graduate School of Science Osaka Metropolitan University 3-3-138 Sugimoto-cho Sumiyoshi-ku Osaka City Osaka558-8585 Japan Inst

The gravitational wave detectors LIGO and Virgo have so far detected gravitational wave signals from 90 compact binary coalescences including two from neutron star binary mergers. Those detections are revolutionizing our understanding of the universe. This ongoing revolution will be accelerated by more accurate localizations of the gravitational wave sources and by longer coincident observation by multi-detectors, which will be made possible using as many detectors as possible. KAGRA is a gravitational wave detector built at Kamioka in Gifu prefecture, Japan, well away from the LIGO and Virgo detectors, with unique features of having cryogenic mirrors and being built underground. KAGRA can be a prototype for next-generation gravitational wave detectors and our experiences benefit those detectors that would have those features to achieve further sensitivity to gravitational waves. In this presentation, the status of KAGRA is given. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gravitational effects

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Calibration of the integrating sphere for O4 in KAGRA gravitational wave telescope. 38

Calibration of the integrating sphere for O4 in KAGRA gravit...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Fujii, Shingo Abe, H. Akutsu, T. Ando, M. Aoumi, M. Araya, A. Aritomi, N. Aso, Y. Bae, S. Bajpai, R. Cannon, K. Cao, Z. Chang, R.-J. Chen, A.H.-Y. Chen, D. Chen, H. Chen, Y. Chiba, A. Chiba, R. Chou, C. Eisenmann, M. Fujii, S. Fukunaga, I. Haba, D. Haino, S. Han, W.-B. Hayakawa, H. Hayama, K. Himemoto, Y. Hirata, N. Hirose, C. Hoshino, S. Hsieh, H.-F. Hsiung, C. Hsu, S.-C. Hui, D.C.Y. Inayoshi, K. Itoh, Y. Iwaya, M. Jin, H.B. Jung, K. Kajita, T. Kamiizumi, M. Kanda, N. Kato, J. Kato, T. Kim, S. Kimura, N. Kiyota, T. Kohri, K. Kokeyama, K. Komori, K. Kong, A.K.H. Koyama, N. Kume, J. Kuroyanagi, S. Kuwahara, S. Kwak, K. Lai, S. Lee, H.W. Lee, R. Lee, S. Leonardi, M. Li, K.L. Lin, L.C.-C. Lin, C.-Y. Lin, E.T. Liu, G.C. Ma, L.-T. Maeda, K. Matsuyama, M. Meyer-Conde, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, S. Miyoki, S. Morisaki, S. Moriwaki, Y. Murakoshi, M. Nakamura, K. Nakano, H. Narikawa, T. Nguyen Quynh, L. Nishino, Y. Nishizawa, A. Obayashi, K. Oh, J.J. Oh, K. Ohashi, M. Ohkawa, M. Oohara, K. Oshima, Y. Oshino, S. Page, M.A. Pan, K.-C. Park, J. Peña Arellano, F.E. Saha, S. Sakai, K. Sako, T. Sato, R. Sato, S. Sato, Y. Sawada, T. Sekiguchi, Y. Shao, L. Shikano, Y. Shimode, K. Shinkai, H. Shiota, J. Somiya, K. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takatani, K. Takeda, H. Takeda, M. Tamaki, M. Tanaka, K. Tanaka, S.J. Tanaka, T. Taruya, A. Tomaru, T. Tomita, K. Tomura, T. Toriyama, A. Trani, A.A. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueno, K. Ushiba, T. van Putten, M.H.P.M. Wang, H. Washimi, T. Wu, C. Wu, H. Yamamoto, K. Yamamoto, M. Yamamoto, T. Yamamoto, T.S. Yamamura, S. Yamazaki, R. Yang, L.-C. Yang, Y. Yeh, S.-W. Yokoyama, J. Yokozawa, T. Yuzurihara, H. Zhao, Y. Zhu, Z.-H. Graduate School of Science Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8551 Japan 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 The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo113-0032 Japan LIGO Hanford Observatory RichlandWA99352 United States 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan 245 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing100875 China Department of Physics National Cheng Kung University No.1 University Road Tainan City701 Taiwan Institute of Physics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu506-1205 Japan Department of Physics National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu30013 Taiwan Faculty of Science University of Toyama 3190 Gofuku Toyama City Toyama930-8555 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa City277-8582 Japan Department of Electrophysics National Yang Ming Chiao Tung University 101 Univ. Street Hsinchu Taiwan Department of Physics Graduate School of Science Osaka Metropolitan University 3-3-138 Sugimoto-cho Sumiyoshi-ku Osaka City Osaka558-8585 Japan Institute of Physics Academia Sinica 128 Sec. 2 Academia Rd. Na

KAGRA, the gravitational wave telescope located in Japan, has started the 4th international observing run called O4 with LIGO and Virgo. The accuracy of parameter estimation for gravitational wave source objects depends on the accuracy of calibration. LIGO, Virgo, and KAGRA use the same calibration method called the photon calibrator (Pcal) method. In the Pcal system, we will obtain the precise displacement of a mirror induced by a well-calibrated radiation pressure of a laser beam which is injected into the mirror. As the uncertainty of the Pcal system is primarily limited by the uncertainty of the laser power measurement, we use integrating sphere (IS) power meters, which are considered to have good accuracy and precision, for the laser power measurement. However, during our calibration measurements in O3GK, we found that there were unidentified systematic errors in the laser power measurement. Therefore, we investigated the incident direction dependence and polarization dependence of the IS power meter. According to our study, the angular dependence differs between two types of ISs, namely GPS (General Purpose Spheres) and LPM (Laser Power Measurement Spheres), which are utilized in our calibration system. The angular dependence of the GPS type was greater than that of the LPM type. The GPS measurement showed an approximate 8.4% increase from the value obtained with perpendicular incidence at maximum. In contrast, the LPM measurement showed a 0.2% increase from the value obtained with perpendicular incidence at maximum. As to polarization dependence, the effect of that on the LPM type was within the range of -0.06% to 0.06%. From this study, we found a possibility that the angle dependence was able to explain the uncertainty observed in O3GK. In this proceeding, we report the angular and polarization dependence of ISs and consider the effect on the uncertainty of the KAGRA Pcal system. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Spheres

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CAMP: Co-Attention Memory Networks for Diagnosis Prediction in Healthcare

CAMP: Co-Attention Memory Networks for Diagnosis Prediction ...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Jingyue Gao Xiting Wang Yasha Wang Zhao Yang Junyi Gao Jiangtao Wang Wen Tang Xing Xie Key Laboratory of High Confidence Software Technologies Ministry of Education School of Electronics Engineering and Computer Science Peking University Microsoft Research Asia National Engineering Research Center of Software Engineering Peking University School of Computing and Communications Lancaster University Peking University Third Hospital

Diagnosis prediction, which aims to predict future health information of patients from historical electronic health records (EHRs), is a core research task in personalized healthcare. Although some RNN-based methods have been proposed to model sequential EHR data, these methods have two major issues. First, they cannot capture fine-grained progression patterns of patient health conditions. Second, they do not consider the mutual effect between important context (e.g., patient demographics) and historical diagnosis. To tackle these challenges, we propose a model called Co-Attention Memory networks for diagnosis Prediction (CAMP), which tightly integrates historical records, fine-grained patient conditions, and demographics with a three-way interaction architecture built on co-attention. Our model augments RNNs with a memory network to enrich the representation capacity. The memory network enables analysis of fine-grained patient conditions by explicitly incorporating a taxonomy of diseases into an array of memory slots. We instantiate the READ/WRITE operations of the memory network so that the memory cooperates effectively with the patient demographics through co-attention mechanism. Experiments on real-world datasets demonstrate that CAMP consistently performs better than state-of-the-art methods.

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