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arXiv 2023年

作者： Cui, Yuzhu Hada, Kazuhiro Kawashima, Tomohisa Kino, Motoki Lin, Weikang Mizuno, Yosuke Ro, Hyunwook Honma, Mareki Yi, Kunwoo Yu, Jintao Park, Jongho Jiang, Wu Shen, Zhiqiang Kravchenko, Evgeniya Algaba, Juan-Carlos Cheng, Xiaopeng Cho, Ilje Giovannini, Gabriele Giroletti, Marcello Jung, Taehyun Lu, Ru-Sen Niinuma, Kotaro Oh, Junghwan Ohsuga, Ken Sawada-Satoh, Satoko Sohn, Bong Won Takahashi, Hiroyuki R. Takamura, Mieko Tazaki, Fumie Trippe, Sascha Wajima, Kiyoaki Akiyama, Kazunori An, Tao Asada, Keiichi Buttaccio, Salvatore Byun, Do-Young Cui, Lang Hagiwara, Yoshiaki Hirota, Tomoya Hodgson, Jeffrey Kawaguchi, Noriyuki Kim, Jae-Young Lee, Sang-Sung Lee, Jee Won Lee, Jeong Ae Maccaferri, Giuseppe Melis, Andrea Melnikov, Alexey Migoni, Carlo Oh, Se-Jin Sugiyama, Koichiro Wang, Xuezheng Zhang, Yingkang Chen, Zhong Hwang, Ju-Yeon Jung, Dong-Kyu Kim, Hyo-Ryoung Kim, Jeong-Sook Kobayashi, Hideyuki Li, Bin Li, Guanghui Li, Xiaofei Liu, Zhiyong Liu, Qinghui Liu, Xiang Oh, Chung-Sik Oyama, Tomoaki Roh, Duk-Gyoo Wang, Jinqing Wang, Na Wang, Shiqiang Xia, Bo Yan, Hao Yeom, Jae-Hwan Yonekura, Yoshinori Yuan, Jianping Zhang, Hua Zhao, Rongbing Zhong, Weiye Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China Tsung-Dao Lee Institute Shanghai Jiao Tong University 520 Shengrong Road Shanghai201210 China Astronomical Science Program The Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Mizusawa VLBI Observatory National Astronomical Observatory of Japan 2-12 Hoshigaoka Mizusawa Iwate Oshu023-0861 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwanoha Chiba Kashiwa277-8582 Japan Kogakuin University of Technology & Engineering Academic Support Center 2665-1 Nakano-machi Hachioji Tokyo192-0015 Japan South-Western Institute For Astronomy Research Yunnan University Kunming650500 China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Institut für Theoretische Physik Goethe-Universität Frankfurt Max-von-Laue-Straße 1 Frankfurt am MainD-60438 Germany Korea Astronomy & Space Science Institute Daedeokdae-ro 776 Yuseong-gu Daejeon34055 Korea Republic of Department of Astronomy Yonsei University Yonsei-ro 50 Seodaemun-gu Seoul03722 Korea Republic of Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Department of Physics and Astronomy Seoul National University Gwanak-gu Seoul08826 Korea Republic of Department of Information Countermeasure Air Force Early Warning Academy Wuhan430019 China Institute of Astronomy and Astrophysics Academia Sinica HiloHI96720 United States Shanghai Astronomical Observatory Chinese Academy of Sciences 80 Nandan Road Shanghai200030 China Key Laboratory of Radio Astronomy Chinese Academy of Sciences Beijing100101 China Moscow Institute of Physics and Technology Dolgoprudny Institutsky per. 9 Moscow141700 Russia Lebedev Physical Institute The Russian Academy of Sciences Leninsky prospekt 53 Moscow119991 Russia Department of Physics Faculty of Science U

The nearby radio galaxy M87 offers a unique opportunity to explore the connections between the central supermassive black hole and relativistic jets. Previous studies of the inner region of M87 revealed a wide opening angle for the jet originating near the black hole 1–4. The Event Horizon Telescope resolved the central radio source and found an asymmetric ring structure consistent with expectations from General Relativity 5. With a baseline of 17 years of observations, there was a shift in the jet’s transverse position, possibly arising from an eight to ten-year quasi-periodicity 3. However, the origin of this sideways shift remains unclear. Here we report an analysis of radio observations over 22 years that suggests a period of about 11 years in the position angle variation of the jet. We infer that we are seeing a spinning black hole that induces the Lense-Thirring precession of a misaligned accretion disk. Similar jet precession may commonly occur in other active galactic nuclei but has been challenging to detect owing to the small magnitude and long period of the variation. Copyright © 2023, The Authors. All rights reserved.

关键词： Active Galactic Nuclei

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Inter-comparison of multiple Global Climate Model (GCM) data based on spatial pattern of rainfall over Indonesia

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IOP Conference Series: Earth and Environmental Science 2019年第1期284卷

作者： Elania Aflahah Arnida Lailatul Latifah Rahmat Hidayat Rini Hidayati Andi Ihwan Applied Climatology Study Program Graduate School Bogor Agricultural University Bogor 16680 Laboratorium of High-Performance Computing Research Center for Informatics Indonesian Institute of Sciences Bogor West Java 16916 Department of Geophysics and Meteorology Bogor Agricultural University Bogor 16680

The Coupled Model Inter-comparison Project Phase 5 (CMIP5) is the output of many coupled atmosphere-ocean of global climate models (GCMs) and widely used for climate research, especially for driving regional climate model. There are more than 40 CMIP5 GCMs data available, but no single model can be considered as the best for every region. The use of CMIP5 GCMs data for rainfall projection in Indonesia is important to improve the accuracy of the monthly and seasonal rainfall forecast. Then, this study evaluates the capability of the CMIP5 GCMs data for Indonesia region by quantitatively comparing the spatial pattern of the precipitation mean and standard deviation of the CMIP5 data against GPCP, GPCC, and CRU data in the period 1980-2005. Furthermore, the composite analysis is conducted to observe the model performance in reproducing the precipitation characteristic over some areas in Indonesia. In conclusion, the models NorESM1-M, NorESM1-ME, GFDL-ESM2M, CSIRO-MK3-6-0 perform the rainfall mean better than others, while the standard deviation of the rainfall show that the models NorESM1-M, BNU-ESM, CMCC-CMS are superior in which NorESM1-M gives the best performance. The annual precipitation pattern of the model NorESM1-M over various areas in Indonesia is also highly correlated with the observations. Thus, the most suitable model for Indonesia region is NorESM1-M.

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Deep Machine Learning Techniques for the Detection and Classification of Sperm Whale Bioacoustics (vol 9, 12588, 2019)

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SCIENTIFIC REPORTS 2019年第1期9卷 12588-12588页

作者： Bermant, Peter C. Bronstein, Michael M. Wood, Robert J. Gero, Shane Gruber, David F. Radcliffe Institute for Advanced Study Harvard University Cambridge MA USA Department of Computing Imperial College London UK Twitter 20 Air Street London W1B 5DL United Kingdom Wyss Institute for Biologically Inspired Engineering Harvard University Cambridge MA USA Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA Department of Zoophysiology Institute for Bioscience Aarhus University C.F. Møllers Allé 3 8000 Aarhus Denmark Department of Natural Sciences Baruch College and The Graduate Center PhD Program in Biology City University of New York New York NY USA

We implemented Machine Learning (ML) techniques to advance the study of sperm whale (Physeter macrocephalus) bioacoustics. This entailed employing Convolutional Neural Networks (CNNs) to construct an echolocation click detector designed to classify spectrograms generated from sperm whale acoustic data according to the presence or absence of a click. The click detector achieved 99.5% accuracy in classifying 650 spectrograms. The successful application of CNNs to clicks reveals the potential of future studies to train CNN-based architectures to extract finer-scale details from cetacean spectrograms. Long short-term memory and gated recurrent unit recurrent neural networks were trained to perform classification tasks, including (1) 'coda type classification' where we obtained 97.5% accuracy in categorizing 23 coda types from a Dominica dataset containing 8,719 codas and 93.6% accuracy in categorizing 43 coda types from an Eastern Tropical Pacific (ETP) dataset with 16,995 codas; (2) 'vocal clan classification' where we obtained 95.3% accuracy for two clan classes from Dominica and 93.1% for four ETP clan types; and (3) 'individual whale identification' where we obtained 99.4% accuracy using two Dominica sperm whales. These results demonstrate the feasibility of applying ML to sperm whale bioacoustics and establish the validity of constructing neural networks to learn meaningful representations of whale vocalizations. [ABSTRACT FROM AUTHOR]

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User interface modelling by implementing storytelling on Sundanese cultural introduction media for early childhood using child-centered design method

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IOP Conference Series: Materials Science and Engineering 2018年第1期434卷

作者： O D J Ayuningtyas V Effendy E R Kaburuan School of Computing Universitas Telkom Bandung Jawa Barat Indonesia Graduate Program Universitas Bina Nusantara Jakarta Indonesia

The introduction of local culture to early age children in Indonesia is very necessary to maintain its sustainability. Several institutions of Early Childhood Education began to introduce local culture to their students, but the limited time and place to be a separate constraint for the activity. Digital media can solve this problem by presenting an introduction to local culture which can be accessed without time and place limitation, but there are some problems of using the existing application because children have their own characteristics and different ways of absorbing a knowledge. From the observation of an early childhood, it is known that children more easily absorb knowledge through playing game and listening to the story telling. Story telling invites children to develop their imagination and more memorable, so that information can be better absorbed. To accommodate the learning need, this research developed the User Interface (UI) by combining a game and a story telling. This modelling involves the participation of early childhood and companions using child-centered design (CCD) methods. The UI model then tested using System Usability Scale (SUS) to measure its usability score and obtained 85.833, which means the children feel satisfied in using the UI model.

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SwapItUp: A Face Swap Application for Privacy Protection

SwapItUp: A Face Swap Application for Privacy Protection

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Sachit Mahajan Ling-Jyh Chen Tzu-Chieh Tsai Department of Computer Science National Chengchi University Social Networks and Human Centered Computing Program Taiwan International Graduate Program Academia Sinica Institute of Information Science

ISBN: (纸本)9781509060306

There is a growing concern over the issues related to online privacy due to large availability of high quality images. To tackle the privacy concerns a face swapping application is proposed. There is a library of face images, which is created by downloading images from different sources on Internet. For any given image, lirst of all facial landmarks are detected. The second image is rotated and scaled so that it can properly lit over the input image. To make sure that the new image looks natural, color balance adjustment is done. After that blending of features from the second image onto the input image is done. It is also shown how this system can be used to creating appealing and funny photographs for entertainment purposes. We conclude with a study that shows the high quality of images produced by this system as compared to existing face swap applications and also limitations of this system.

关键词： Face Image color analysis Three-dimensional displays Solid modeling Skin Privacy Image resolution

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Linguistic based steganography using lexical substitution and syntactical transformation 6

Linguistic based steganography using lexical substitution an...

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6th International Conference on IT Convergence and Security, ICITCS 2016

作者： Barmawi, Ari Informatics Graduate Program School of Computing Telkom University Bandung Indonesia

ISBN: (纸本)9781509037643

Recently, secure information transmission is necessary such that no one can detect information sent via an open channel. In 2013, Chang and Clark proposed a method using lexical substitution and vertex coding for securing the information exchange between parties, such that no one can detect the exchanged information. However, the maximum payload capacity was still 2 bits. This work proposed a method for increasing the payload capacity of Chang's method by applying additional syntactical transformation instead of only lexical substitution and vertex coding. Based on the implementation, the payload resulted by the proposed method may increase minimum 2 bits, such that the minimum payload size is 4 bits, which is greater than Chang's method. © 2016 IEEE.

关键词： Steganography

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The ALMA Survey of Star Formation and Evolution in Massive Protoclusters with Blue Profiles (ASSEMBLE): Core Growth, Cluster Contraction, and Primordial Mass Segregation

arXiv

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arXiv 2023年

作者： Xu, Fengwei Wang, Ke Liu, Tie Tang, Mengyao Evans, Neal J. Palau, Aina Morii, Kaho He, Jinhua Sanhueza, Patricio Liu, Hong-Li Stutz, Amelia Zhang, Qizhou Chen, Xi Li, Pak Shing Gómez, Gilberto C. Vázquez-Semadeni, Enrique Li, Shanghuo Mai, Xiaofeng Lu, Xing Liu, Meizhu Chen, Li Li, Chuanshou Shi, Hongqiong Ren, Zhiyuan Li, Di Garay, Guido Bronfman, Leonardo Dewangan, Lokesh Juvela, Mika Lee, Chang Won Zhang, S. Yue, Nannan Wang, Chao Ge, Yifei Jiao, Wenyu Luo, Qiuyi Zhou, J.-W. Tatematsu, Kenichi Chibueze, James O. Su, Keyun Sun, Shenglan Ristorcelli, I. Toth, L. Viktor Kavli Institute for Astronomy and Astrophysics Peking University Beijing100871 China Department of Astronomy School of Physics Peking University Beijing100871 China Shanghai Astronomical Observatory Chinese Academy of Sciences 80 Nandan Road Shanghai200030 China Institute of Astrophysics School of Physics and Electronic Science Chuxiong Normal University Chuxiong675000 China Department of Astronomy The University of Texas at Austin 2515 Speedway Stop C1400 AustinTX78712-1205 United States Instituto de Radioastronomía y Astrofísica Universidad Nacional Autónoma de México Antigua Carretera a Pátzcuaro 8701 Ex-Hda. San José de la Huerta Morelia Michoacán58089 Mexico Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan National Astronomical Observatory of Japan National Institutes of Natural Sciences 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Yunnan Observatories Chinese Academy of Sciences 396 Yangfangwang Guandu District Kunming650216 China Chinese Academy of Sciences South AmericaCenterfor Astronomy National Astronomical Observatories CAS Beijing100101 China Departamento de Astronomía Universidad de Chile Las Condes Santiago7591245 Chile Astronomical Science Program The Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Department of Astronomy Yunnan University Kunming650091 China Departamento de Astronomía Universidad de Concepción Casilla 160-C Concepción Chile Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Center for Astrophysics Guangzhou University Guangzhou510006 China Peng Cheng Lab Shenzhen518066 China Max Planck Institute for Astronomy Königstuhl 17 HeidelbergD-69117 Germany National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China National Astronomical Observatories CAS 20A Datun Road Chaoyang District Beijing100101 China Research

The ALMA Survey of Star Formation and Evolution in Massive Protoclusters with Blue Profiles (ASSEMBLE) aims to investigate the process of mass assembly and its connection to high-mass star formation theories in protoclusters in a dynamic view. We observed 11 massive (Mclump 103 M☉), luminous (Lbol 104 L☉), and blue-profile (infall signature) clumps by ALMA with resolution of ∼2200–5500 au (median value of 3500 au) at 350 GHz (870 µm). 248 dense cores were identified, including 106 cores showing protostellar signatures and 142 prestellar core candidates. Compared to early-stage infrared dark clouds (IRDCs) by ASHES, the core mass and surface density within the ASSEMBLE clumps exhibited significant increment, suggesting concurrent core accretion during the evolution of the clumps. The maximum mass of prestellar cores was found to be 2 times larger than that in IRDCs, indicating that evolved protoclusters have the potential to harbor massive prestellar cores. The mass relation between clumps and their most massive core (MMCs) is observed in ASSEMBLE but not in IRDCs, which is suggested to be regulated by multiscale mass accretion. The mass correlation between the core clusters and their MMCs has a steeper slope compared to that observed in stellar clusters, which can be due to fragmentation of the MMC and stellar multiplicity. We observe a decrease in core separation and an increase in central concentration as protoclusters evolve. We confirm primordial mass segregation in the ASSEMBLE protoclusters, possibly resulting from gravitational concentration and/or gas accretion. © 2023, CC BY.

关键词： Segregation (metallography)

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The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

arXiv

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arXiv 2023年

作者： Ma, Jun Xie, Ronald Ayyadhury, Shamini Ge, Cheng Gupta, Anubha Gupta, Ritu Gu, Song Zhang, Yao Lee, Gihun Kim, Joonkee Lou, Wei Li, Haofeng Upschulte, Eric Dickscheid, Timo de Almeida, José Guilherme Wang, Yixin Han, Lin Yang, Xin Labagnara, Marco Gligorovski, Vojislav Scheder, Maxime Rahi, Sahand Jamal Kempster, Carly Pollitt, Alice Espinosa, Leon Mignot, Tâm Middeke, Jan Moritz Eckardt, Jan-Niklas Li, Wangkai Li, Zhaoyang Cai, Xiaochen Bai, Bizhe Greenwald, Noah F. Van Valen, David Weisbart, Erin Cimini, Beth A. Cheung, Trevor Brück, Oscar Bader, Gary D. Wang, Bo Peter Munk Cardiac Centre University Health Network TorontoON Canada Department of Laboratory Medicine and Pathobiology University of Toronto TorontoON Canada Vector Institute TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Donnelly Centre University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada School of Medicine and Pharmacy Ocean University of China Qingdao China New Delhi India Laboratory Oncology Dr. BRA-IRCH All India Institute of Medical Sciences New Delhi India Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing China Shanghai Artificial Intelligence Laboratory Shanghai China Graduate School of AI KAIST Seoul Korea Republic of Shenzhen Research Institute of Big Data Shenzhen China Shenzhen China Helmholtz AI Research Center Jülich Jülich Germany Faculty of Mathematics and Natural Sciences Institute of Computer Science Heinrich Heine University Düsseldorf Düsseldorf Germany Hinxton United Kingdom Champalimaud Foundation - Centre for the Unknown Lisbon Portugal Department of Bioengineering Stanford University Palo AltoCA United States Tandon School of Engineering New York University New YorkNY United States School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lausanne Switzerland School of Biological Sciences University of Reading Reading United Kingdom Laboratoire de Chimie Bactérienne CNRS Université Aix Marseille UMR Institut de Microbiologie de la Méditerranée Marseille France Department of Internal Medicine I University Hospital Dresden Technical University Dresden Dresden Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Department of Automation University of Science and Technology of China Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei Chi

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging. © 2023, CC BY-NC-ND.

关键词： Deep learning

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Input optics systems of the KAGRA detector during O3GK (vol 2023, 023F01, 2023)

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PROGRESS OF THEORETICAL AND EXPERIMENTAL PHYSICS 2023年第5期2023卷

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, Ws 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. Quynh, L. Nguyen Ni, W-T Nishizawa, A. Nozaki, S. Obuchi, Y. Ogaki, W. Oh, J. J. 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. Arellano, F. E. Pena Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Sawada, T. Sekiguchi, T. Sekiguchi, Y. Shao, L. Shibagaki, S. Shimizu, R. Shimoda, T. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Son, E. J. Sotani, H. Sugimoto, R. Suresh, J. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Graduate School of Science and Technology Hirosaki University 3 Bunkyo-cho Hirosaki Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information 245 Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Republic of Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Road Danshui Dist. New Taipei City 25137 Taiwan Department of Physics

KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 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 kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.

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Problem-based learning methodology applied within a data network infrastructure design course a real case implementation

Problem-based learning methodology applied within a data net...

引用

Iberian Conference on Information Systems and Technologies (CISTI)

作者： Valéria Farinazzo Martins Paulo N. M. Sampaio Antônio José A. Cordeiro Bruno Ferreira Viana Mackenzie Prebisterian University Computing and Systems Graduate Program Salvador University (UNIFACS) Computational Modelling and Industrial Technology Senai - Cimatec Management and Technology Graduate Professional Program (GESTEC) Bahia State Estácio University (Estácio FIB)

Education professionals are always searching for new ways of promoting learning, either by modifying the pedagogical project of courses or by the adoption of new learning strategies. In particular, this paper presents the results of an effort in order to bridge the knowledge acquired by students within classroom in face-to-face classes with technical skills required in real life situations. The contribution presented in this paper is the result of an assignment applied within an undergraduate Data Network Infrastructure Design course in a Brazilian university using an adapted Problem-Based Learning methodology (PBL), as a motivational tool. This paper also presents and discusses the resulting data related to the learning assessment.

关键词： Problem-solving Education Computer networks Electronic mail Laboratories Bridges Tools

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