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Observation of Spectral Structures in the Flux of Cosmic-Ray Protons from 50 GeV to 60 TeV with the Calorimetric Electron Telescope on the International Space Station

arXiv

引用

arXiv 2022年

作者： Adriani, O. Akaike, Y. Asano, K. Asaoka, Y. Berti, E. Bigongiari, G. Binns, W.R. Bongi, M. Brogi, P. Bruno, A. Buckley, J.H. Cannady, N. Castellini, G. Checchia, C. Cherry, M.L. Collazuol, G. Ebisawa, K. Ficklin, A.W. Fuke, H. Gonzi, S. Guzik, T.G. Hams, T. Hibino, K. Ichimura, M. Ioka, K. Ishizaki, W. Israel, M.H. Kasahara, K. Kataoka, J. Kataoka, R. Katayose, Y. Kato, C. Kawanaka, N. Kawakubo, Y. Kobayashi, Kazuyoshi Kohri, K. Krawczynski, H.S. Krizmanic, J.F. Maestro, P. Marrocchesi, P.S. Messineo, A.M. Mitchell, J.W. Miyake, S. Moiseev, A.A. Mori, M. Mori, N. Motz, H.M. Munakata, K. Nakahira, S. Nishimura, J. de Nolfo, G.A. Okuno, S. Ormes, J.F. Ozawa, S. Pacini, L. Papini, P. Rauch, B.F. Ricciarini, S.B. Sakai, K. Sakamoto, T. Sasaki, M. Shimizu, Y. Shiomi, A. Spillantini, P. Stolzi, F. Sugita, S. Sulaj, A. Takita, M. Tamura, T. Terasawa, T. Torii, S. Tsunesada, Y. Uchihori, Y. Vannuccini, E. Wefel, J.P. Yamaoka, K. Yanagita, S. Yoshida, A. Yoshida, K. Zober, W.V. Department of Physics University of Florence Via Sansone 1 Sesto Fiorentino50019 Italy INFN Sezione di Florence Via Sansone 1 Sesto Fiorentino50019 Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Ibaraki Tsukuba305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa277-8582 Japan Department of Physical Sciences Earth and Environment University of Siena via Roma 56 Siena53100 Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3 Pisa56127 Italy Department of Physics McDonnell Center for the Space Sciences Washington University One Brookings Drive St. LouisMO63130-4899 United States Heliospheric Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Astroparticle Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Research and Exploration in Space Sciences and Technology NASA GSFC GreenbeltMD20771 United States Via Madonna del Piano 10 Sesto Fiorentino50019 Italy Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States Department of Physics and Astronomy University of Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Kanagawa Sagamihara252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Yokohama221-8686 Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki University 3 Bunkyo Aomori Hirosaki036-8561 Japan Yukawa Institute for Theoretical Physics Kyoto Univers

A precise measurement of the cosmic-ray proton spectrum with the Calorimetric Electron Telescope (CALET) is presented in the energy interval from 50 GeV to 60 TeV and the observation of a softening of the spectrum above 10 TeV is reported. The analysis is based on the data collected during ∼6.2 years of smooth operations aboard the International Space Station (ISS) and covers a broader energy range with respect to the previous proton flux measurement by CALET, with an increase of the available statistics by a factor of ∼2.2. Above a few hundred GeV we confirm our previous observation of a progressive spectral hardening with a higher significance (more than 20 sigma). In the multi-TeV region we observe a second spectral feature with a softening around 10 TeV and a spectral index change from −2.6 to −2.9 consistently, within the errors, with the shape of the spectrum reported by DAMPE. We apply a simultaneous fit of the proton differential spectrum which well reproduces the gradual change of the spectral index encompassing the lower energy power-law regime and the two spectral features observed at higher energies. Copyright © 2022, The Authors. All rights reserved.

关键词： Cosmology

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Cosmic-ray Boron Flux Measured from 8.4 GeV/n to 3.8 TeV/n with the Calorimetric Electron Telescope on the International Space Station

arXiv

引用

arXiv 2022年

作者： Adriani, O. Akaike, Y. Asano, K. Asaoka, Y. Berti, E. Bigongiari, G. Binns, W.R. Bongi, M. Brogi, P. Bruno, A. Buckley, J.H. Cannady, N. Castellini, G. Checchia, C. Cherry, M.L. Collazuol, G. de Nolfo, G.A. Ebisawa, K. Ficklin, A.W. Fuke, H. Gonzi, S. Guzik, T.G. Hams, T. Hibino, K. Ichimura, M. Ioka, K. Ishizaki, W. Israel, M.H. Kasahara, K. Kataoka, J. Kataoka, R. Katayose, Y. Kato, C. Kawanaka, N. Kawakubo, Y. Kobayashi, K. Kohri, K. Krawczynski, H.S. Krizmanic, J.F. Maestro, P. Marrocchesi, P.S. Messineo, A.M. Mitchell, J.W. Miyake, S. Moiseev, A.A. Mori, M. Mori, N. Motz, H.M. Munakata, K. Nakahira, S. Nishimura, J. Okuno, S. Ormes, J.F. Ozawa, S. Pacini, L. Papini, P. Rauch, B.F. Ricciarini, S.B. Sakai, K. Sakamoto, T. Sasaki, M. Shimizu, Y. Shiomi, A. Spillantini, P. Stolzi, F. Sugita, S. Sulaj, A. Takita, M. Tamura, T. Terasawa, T. Torii, S. Tsunesada, Y. Uchihori, Y. Vannuccini, E. Wefel, J.P. Yamaoka, K. Yanagita, S. Yoshida, A. Yoshida, K. Zober, W.V. Department of Physics University of Florence Via Sansone Sesto Fiorentino1 - 50019 Italy INFN Sezione di Florence Via Sansone Sesto Fiorentino1 - 50019 Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Ibaraki Tsukuba305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba277-8582 Japan Department of Physical Sciences Earth and Environment University of Siena via Roma 56 Siena53100 Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo Pisa3 - 56127 Italy Department of Physics McDonnell Center for the Space Sciences Washington University One Brookings Drive St. LouisMO63130-4899 United States Heliospheric Physics Laboratory NASA/GSFC GreenbeltMD20771 United States Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Astroparticle Physics Laboratory NASA/GSFC GreenbeltMD20771 United States Center for Research and Exploration in Space Sciences and Technology NASA/GSFC GreenbeltMD20771 United States Via Madonna del Piano 10 Sesto Fiorentino50019 Italy Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States Department of Physics and Astronomy University of Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Sagamihara Kanagawa252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Yokohama Kanagawa221-8686 Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki University 3 Bunkyo Hirosaki Aomori036-8561 Japan Yukawa Institute for Theoretical Physics Kyo

We present the measurement of the energy dependence of the boron flux in cosmic rays and its ratio to the carbon flux in an energy interval from 8.4 GeV/n to 3.8 TeV/n based on the data collected by the CALorimetric Electron Telescope (CALET) during ∼ 6.4 years of operation on the International Space Station. An update of the energy spectrum of carbon is also presented with an increase in statistics over our previous measurement. The observed boron flux shows a spectral hardening at the same transition energy E0 ∼ 200 GeV/n of the C spectrum, though B and C fluxes have different energy dependences. The spectral index of the B spectrum is found to be γ = −3.047 ± 0.024 in the interval 25 Copyright © 2022, The Authors. All rights reserved.

关键词： Cosmic rays

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Framing image registration as a landmark detection problem for label-noise-aware task representation (HitR)

arXiv

引用

arXiv 2023年

作者： Waldmannstetter, Diana Ezhov, Ivan Wiestler, Benedikt Campi, Francesco Kukuljan, Ivan Ehrlich, Stefan Vinayahalingam, Shankeeth Baheti, Bhakti Chakrabarty, Satrajit Baid, Ujjwal Bakas, Spyridon Schwarting, Julian Metz, Marie Kirschke, Jan S. Rueckert, Daniel Heckemann, Rolf A. Piraud, Marie Menze, Bjoern H. Kofler, Florian Department of Computer Science TUM School of Computation Information and Technology Technical University of Munich Munich Germany Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Germany Helmholtz AI Helmholtz Munich Neuherberg Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Healthcare Technologies SETLabs Research Munich Germany Department of Oral and Maxillofacial Surgery Radboud University Nijmegen Medical Centre Nijmegen Netherlands Division of Computational Pathology Department of Pathology and Laboratory Medicine School of Medicine Indiana University IndianapolisIN United States Department of Electrical and Systems Engineering Washington University in St.Louis St. LouisMO United States Artificial Intelligence in Healthcare and Medicine Technical University of Munich Munich Germany Department of Computing Imperial College London London United Kingdom Department of Medical Radiation Sciences University of Gothenburg Gothenburg Sweden

Accurate image registration is pivotal in bio-medical image analysis, where selecting suitable registration algorithms demands careful consideration. While numerous algorithms are available, the evaluation metrics to assess their performance have remained relatively static. This study addresses this challenge by introducing a novel evaluation metric termed Landmark Hit Rate (HitR), which focuses on the clinical relevance of image registration accuracy. Unlike traditional metrics such as Target Registration Error, which emphasize sub-resolution differences, HitR considers whether registration algorithms successfully position landmarks within defined confidence zones. This paradigm shift acknowledges the inherent annotation noise in medical images, allowing for more meaningful assessments. To equip HitR with label-noise-awareness, we propose defining these confidence zones based on an Inter-rater Variance analysis. Consequently, hit rate curves are computed for varying landmark zone sizes, enabling performance measurement for a task-specific level of accuracy. Our approach offers a more realistic and meaningful assessment of image registration algorithms, reflecting their suitability for clinical and biomedical applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Medical imaging

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Rectenna for Bluetooth Low Energy Applications

Rectenna for Bluetooth Low Energy Applications

引用

IEEE Wireless Power Transfer Conference (WPTC)

作者： Boules A. Mouris Wael Elshennawy Panagiotis Petridis Yuan Ding Spyridon N. Daskalakis Division of Information Science and Engineering KTH Royal Institute of Technology Stockholm Sweden Orange Business Services Orange Cairo Egypt Institute of Sensors Signals and Systems Heriot-Watt University Edinburgh United Kingdom

ISBN: (数字)9781728107059

ISBN: (纸本)9781728107066

In this paper, we propose an efficient rectenna design for Bluetooth low energy (BLE) applications targeting the 2.4 GHz ISM band. A miniature meandered planar Inverted-F antenna (MIFA) was designed, simulated, fabricated, and measured, achieving good matching with small profile. In addition, a single-diode rectifier circuit was optimized at - 20 dBm input power to convert the radio frequency (RF) energy captured by the antenna into DC power. Simulation results for the rectifier circuit show that it maintains a high RF-to-DC conversion efficiency. Using ideal components, an efficiency of 36 % can be achieved at - 20 dBm input power. When the non-idealities are considered in the rectifier, an efficiency of 20 % at - 20 dBm input power can be obtained.

关键词： Rectenna Energy Harvesting Bluetooth Low Energy (BLE) Rectennas energy harvesting rectifying circuits Bluetooth LOW ENERGY Conversion efficiency

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CALET Search for electromagnetic counterparts of gravitational waves during the LIGO/Virgo O3 run

arXiv

引用

arXiv 2022年

作者： Adriani, O. Akaike, Y. Asano, K. Asaoka, Y. Berti, E. Bigongiari, G. Binns, W.R. Bongi, M. Brogi, P. Bruno, A. Buckley, J.H. Cannady, N. Castellini, G. Checchia, C. Cherry, Michael L. Collazuol, G. Ebisawa, K. Ficklin, A.W. Fuke, H. Gonzi, S. Guzik, T.G. Hams, T. Hibino, K. Ichimura, M. Ioka, K. Ishizaki, W. Israel, M.H. Kasahara, K. Kataoka, J. Kataoka, R. Katayose, Y. Kato, C. Kawanaka, N. Kawakubo, Yuta Kobayashi, K. Kohri, K. Krawczynski, H.S. Krizmanic, J.F. Maestro, P. Marrocchesi, P.S. Messineo, A.M. Mitchell, J.W. Miyake, S. Moiseev, A.A. Mori, M. Mori, N. Motz, H.M. Munakata, K. Nakahira, S. Nishimura, J. de Nolfo, G.A. Okuno, S. Ormes, J.F. Ospina, N. Ozawa, S. Pacini, L. Papini, P. Rauch, B.F. Ricciarini, S.B. Sakai, K. Sakamoto, T. Sasaki, M. Shimizu, Y. Shiomi, A. Spillantini, P. Stolzi, F. Sugita, S. Sulaj, A. Takita, M. Tamura, T. Terasawa, T. Torii, S. Tsunesada, Y. Uchihori, Y. Vannuccini, E. Wefel, J.P. Yamaoka, K. Yanagita, S. Yoshida, A. Yoshida, K. Zober, W.V. Department of Physics University of Florence Via Sansone 1 Sesto Fiorentino 50019 Italy INFN Sezione di Florence Via Sansone 1 Sesto Fiorentino 50019 Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Ibaraki Tsukuba305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba277-8582 Japan Department of Physical Sciences Earth and Environment University of Siena via Roma 56 Siena53100 Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3 Pisa56127 Italy Department of Physics McDonnell Center for the Space Sciences Washington University One Brookings Drive St. LouisMO63130-4899 United States Heliospheric Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Astroparticle Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Research and Exploration in Space Sciences and Technology NASA GSFC GreenbeltMD20771 United States Via Madonna del Piano 10 Sesto Fiorentino 50019 Italy Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States Department of Physics and Astronomy University of Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Kanagawa Sagamihara252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Yokohama221-8686 Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki University 3 Bunkyo Aomori Hirosaki036-8561 Japan Yukawa Institute for Theoretical Physics Kyoto Univ

The CALorimetric Electron Telescope (CALET) on the International Space Station (ISS) consists of a high-energy cosmic ray CALorimeter (CAL) and a lower-energy CALET Gamma ray Burst Monitor (CGBM). CAL is sensitive to electrons up to 20 TeV, cosmic ray nuclei from Z = 1 through Z ∼ 40, and gamma rays over the range 1 GeV - 10 TeV. CGBM observes gamma rays from 7 keV to 20 MeV. The combined CAL-CGBM instrument has conducted a search for gamma ray bursts (GRBs) since Oct. 2015. We report here on the results of a search for X-ray/gamma ray counterparts to gravitational wave events reported during the LIGO/Virgo observing run O3. No events have been detected that pass all acceptance criteria. We describe the components, performance, and triggering algorithms of the CGBM - the two Hard X-ray Monitors (HXM) consisting of LaBr3(Ce) scintillators sensitive to 7 keV to 1 MeV gamma rays and a Soft Gamma ray Monitor (SGM) BGO scintillator sensitive to 40 keV to 20 MeV - and the high-energy CAL consisting of a CHarge-Detection module (CHD), IMaging Calorimeter (IMC), and fully active Total Absorption Calorimeter (TASC). The analysis procedure is described and upper limits to the time-averaged fluxes are presented. Copyright © 2022, The Authors. All rights reserved.

关键词： Gamma rays

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Learning-based Offloading of Tasks with Diverse Delay Sensitivities for Mobile Edge Computing

Learning-based Offloading of Tasks with Diverse Delay Sensit...

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IEEE Global Communications Conference

作者： Tianyu Zhang Yi-Han Chiang Cristian Borcea Yusheng Ji Department of Informatics SOKENDAI (The Graduate University for Advanced Studies) Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan Department of Computer Science New Jersey Institute of Technology NJ USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

The ever-evolving mobile applications need more and more computing resources to smooth user experience and sometimes meet delay requirements. Therefore, mobile devices (MDs) are gradually having difficulties to complete all tasks in time due to the limitations of computing power and battery life. To cope with this problem, mobile edge computing (MEC) systems were created to help with task processing for MDs at nearby edge servers. Existing works have been devoted to solving MEC task offloading problems, including those with simple delay constraints, but most of them neglect the coexistence of deadline-constrained and delay-sensitive tasks (i.e., the diverse delay sensitivities of tasks). In this paper, we propose an actor-critic based deep reinforcement learning (ADRL) model that takes the diverse delay sensitivities into account and offloads tasks adaptively to minimize the total penalty caused by deadline misses of deadline-constrained tasks and the lateness of delay-sensitive tasks. We train the ADRL model using a real data set that consists of the diverse delay sensitivities of tasks. Our simulation results show that the proposed solution outperforms several heuristic algorithms in terms of total penalty, and it also retains its performance gains under different system settings.

关键词： Task analysis Delays Sensitivity Computational modeling Edge computing Load modeling Mobile handsets

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Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

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Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

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Preventing bad behavior in academia

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四川生理科学杂志 2024年第7期46卷 1615-1615页

作者： Rayane da Cruz Albino Faculty of Pharmacy Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil. Department of Host-Microbe Interactions St. Jude Children’s Research Hospital Memphis TN USA. School of the Environment The University of Queensland Whiterock QLD Australia. KU Leuven Ghent Belgium. Laboratory for Computational Social Systems Indraprastha Institute of Information Technology Delhi New Delhi India. University Medical College Shantou Guangdong China. Department of Ecoscience Aarhus Universitet Aarhus Denmark. Institute of Environment and Sustainable Development Banaras Hindu University Varanasi Uttar Pradesh India. Department of Medical Parasitology Faculty of Medicine and Health Sciences Sana’a University Sana’a Yemen and Tropical Disease Research Center Faculty of Medicine and Health Sciences University of Science and Technology Sana’a Yemen. Department of Medicine University of Montreal Montreal QC Canada. Electricity Infrastructure and Buildings Division Pacific Northwest National Laboratory Portland OR USA. Department of Biological Sciences University of New Brunswick Saint John Saint John NB Canada. Department of Biomedical Engineering The University of Melbourne Melbourne VIC Australia. Vagelos Molecular Life Sciences Program University of Pennsylvania Philadelphia PA USA. Doctoral Program in Neurobiology and Behavior Columbia University New York NY USA. Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA. Department of Engineering University of Cambridge Cambridge Cambridgeshire UK. Department of Geography Liverpool John Moores University Liverpool UK. Department of Biology Stanford University Stanford CA USA. Department of Psychology University of Nicosia Nicosia Cyprus. Department of Global Ecology Carnegie Institution for Science Stanford CA USA. Research and Support Division Stellenbosch University Cape Town South Africa.

We gave young scientists this prompt:Describe one change to scientific policy or culture that would substantially decrease incidents of scientific misconduct or other unethical behavior.

关键词： behavior. prompt culture

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Understanding metric-related pitfalls in image analysis validation

arXiv

引用

arXiv 2023年

作者： Reinke, Annika Tizabi, Minu D. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Kavur, A. Emre Rädsch, Tim Sudre, Carole H. Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Buettner, Florian Cardoso, M. Jorge Cheplygina, Veronika Chen, Jianxu Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kleesiek, Jens Kofler, Florian Kooi, Thijs Kopp-Schneider, Annette Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Riegler, Michael A. Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. van Calster, Ben Varoquaux, Gaël Yaniv, Ziv R. Jäger, Paul F. Maier-Hein, Lena Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg A Partnership Between DKFZ University Medical Center Heidelberg Germany Heidelberg Division of Medical Image Computing Germany Heidelberg Division of Intelligent Medical Systems Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montreal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Leuven Belgium partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany and Frankfurt Cancer Insititute Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for Statistics in Medicine University of Oxford Oxford United Kingdom Center for Biomedical In

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately. While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. While focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation. © 2023, CC BY.

关键词： Computer vision

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A study for Motion-Planning Method Resident-tracking Robot based on Reinforcement Learning 30

A study for Motion-Planning Method Resident-tracking Robot b...

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30th International Symposium on Micro-NanoMechatronics and Human science, MHS 2019

作者： Sugimoto, Masashi Yoshioka, Takashi Ishii, Kohei Nonaka, Shogo Deguchi, Mikio Tsuzuki, Shinji Hiran, Masatsugu Electrical and Electronic Engineering Course Ehime University Division of Electrical and Electronic Engineering and Computer Science 3 Bunkyo-cho Matsuyama City Ehime Pref.790-8577 Japan National Institute of Technology Kagawa College Department of Electrical and Computer Engineering 355 Chokushi-cho Takamatsu City Kagawa Pref.761-8058 Japan National Institute of Technology Kagawa College. Department of Electro-Mechanical Systems Engineering 355 Chokushi-cho Takamatsu City Kagawa Pref.761-8058 Japan National Institute of Technology Tsuyama College Department of Integrated Science and Technology 624-1 Numa Tsuyama City Okayama Pref.790-8577 Japan National Institute of Technology Niihama College Department of Electronics and Control Engineering 7-1 Yakumo-cho Niihama City Ehime Pref.790-8580 Japan National Institute of Technology Niihama College Department of Electrical Engineering and Information Science 7-1 Yakumo-cho Niihama City Ehime Pref.792-8580 Japan

ISBN: (纸本)9781728126746

Among the advanced countries, especially in Japan, we are facing on the decreasing birthrate and aging population ahead of the world. In recent, population of single-living elder, and elderly people have been taking care by same-aged person, have been actualized. Unfortunately, the population of caregivers is decreasing according to year. In this situation, the Elderly Person Watching System has been focused on. Especially, Robotics, Internet of Things, and Artificial Intelligence technology have been having high affinity with this system. In this study, firstly, the person watching robot system will be developed. In detail, in this paper, the flexible-analyze system will be focused on. In the algorithm, a resident-tracking task and an energy-saving task are holding. The whole tasks are working based on Reinforcement Learning. Thus, the behavior algorithm of the person watching robot system will be developed. In detail, in this paper, the flexible-analyze system will be focused on. In the algorithm, a resident-tracking task and an energy-saving task are holding. From the verification experiment, the simulation results showed the proposed method has been acquired actions to switch the desired task. © 2019 IEEE.

关键词： Reinforcement learning

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