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6th IEEE International Conference on Communications and Electronics, IEEE ICCE 2016

作者： Quyen, Nguyen Xuan Nguyen, Chuyen T. Barlet-Ros, Pere Dojen, Reiner School of Electronics and Telecommunications Hanoi University of Science and Technology Viet Nam Department of Computer Architecture UPC BarcelonaTech Spain Department of Electronic and Computer Engineering University of Limerick Ireland

ISBN: (纸本)9781509019311

In this paper, we propose a novel approach to the enhancement of physical layer security for chaotic direct-sequence spread-spectrum (DSSS) communication systems. The main idea behind our proposal is to vary the symbol period according to the behavior of the chaotic spreading sequence. As a result, the symbol period and the spreading sequence vary chaotically at the same time. This simultaneous variation aims at protecting DSSS-based communication systems from the blind estimation attacks in the detection of the symbol period. Discrete-Time models for spreading and despreading schemes are presented and analyzed. Multiple access performance of the proposed technique in the presence of additional white Gaussian noise (AWGN) is determined by computer simulations. The increase in security at the physical layer is also evaluated by numerical results. Obtained results show that our proposed technique can protect the system against attacks based on the detection of the symbol period, even if the intruder has full information on the used chaotic sequence. © 2016 IEEE.

关键词： Gaussian noise (electronic)

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Search for secluded dark matter towards the Galactic Centre with the ANTARES neutrino telescope

arXiv

引用

arXiv 2022年

作者： Albert, A. Alves, S. André, M. Anghinolfi, M. Anton, G. Ardid, M. Ardid, S. Aubert, J.-J. Aublin, J. Baret, B. Basa, S. Belhorma, B. Bendahman, M. Benfenati, F. Bertin, V. Biagi, S. Bissinger, M. Boumaaza, J. Bouta, M. Bouwhuis, M.C. Brânzaş, H. Bruijn, R. Brunner, J. Busto, J. Caiffi, B. Calvo, D. Capone, A. Caramete, L. Carr, J. Carretero, V. Celli, S. Chabab, M. Chau, T.N. Cherkaoui El Moursli, R. Chiarusi, T. Circella, M. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Díaz, A.F. de Wasseige, G. Distefano, C. Di Palma, I. Domi, A. Donzaud, C. Dornic, D. Drouhin, D. Eberl, T. van Eeden, T. van Eijk, D. El Khayati, N. Enzenhöfer, A. Fermani, P. Ferrara, G. Filippini, F. Fusco, L. Gatelet, Y. Gay, P. Glotin, H. Gozzini, R. Gracia Ruiz, R. Graf, K. Guidi, C. Hallmann, S. van Haren, H. Heijboer, A.J. Hello, Y. Hernández-Rey, J.J. Hößl, J. Hofestädt, J. Huang, F. Illuminati, G. James, C.W. Jisse-Jung, B. de Jong, M. de Jong, P. Kadler, M. Kalekin, O. Katz, U. Khan-Chowdhury, N.R. Kouchner, A. Kreykenbohm, I. Kulikovskiy, V. Lagunas Gualda, C. Lahmann, R. Le Breton, R. LeStum, S. Lefèvre, D. Leonora, E. Levi, G. Lincetto, M. Lopez-Coto, D. Loucatos, S. Maderer, L. Manczak, J. Marcelin, M. Margiotta, A. Marinelli, A. Martínez-Mora, J.A. Martino, B. Melis, K. Migliozzi, P. Moussa, A. Muller, R. Nauta, L. Navas, S. Nezri, E. Fearraigh, B.Ó. Paun, A. Pavalaş, G.E. Pellegrino, C. Perrin-Terrin, M. Pestel, V. Piattelli, P. Pieterse, C. Poirè, C. Popa, V. Pradier, T. Randazzo, N. Real, D. Reck, S. Riccobene, G. Romanov, A. Sala, F. Sánchez-Losa, A. Salesa Greus, F. Samtleben, D.F.E. Sanguineti, M. Sapienza, P. Schnabel, J. Schumann, J. Schüssler, F. Seneca, J. Spurio, M. Stolarczyk, Th. Taiuti, M. Tayalati, Y. Tingay, S.J. Vallage, B. Van Elewyck, V. Versari, F. Viola, S. Vivolo, D. Wilms, J. Zavatarelli, S. Zegarelli, A. Zornoza, J.D. Zúñiga, J. Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Université de Haute Alsace MulhouseF-68100 France c/ Catedrático José Beltrán Paterna Valencia2 E-46980 Spain Technical University of Catalonia Laboratory of Applied Bioacoustics Rambla Exposició Vilanova i la Geltrú Barcelona08800 Spain INFN - Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Centre for Astroparticle Physics Erwin-Rommel-Str. 1 Erlangen91058 Germany Universitat Politècnica de València C/ Paranimf 1 Gandia46730 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France Université de Paris CNRS Astroparticule et Cosmologie ParisF-75013 France Aix Marseille Univ CNRS CNES LAM Marseille France National Center for Energy Sciences and Nuclear Techniques B.P.1382 R. P.10001 12 Morocco University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco INFN - Sezione di Bologna Viale Berti-Pichat 6/2 Bologna40127 Italy Dipartimento di Fisica e Astronomia dell’Università Viale Berti Pichat 6/2 Bologna40127 Italy Via S. Sofia 62 Catania95123 Italy Laboratory of Physics of Matter and Radiations B.P.717 Oujda6000 Morocco Nikhef Science Park Amsterdam Netherlands Institute of Space Science Bucharest MagureleRO-077125 Romania Universiteit van Amsterdam Instituut voor Hoge-Energie Fysica Science Park 105 Amsterdam1098 XG Netherlands INFN - Sezione di Roma P.le Aldo Moro 2 Roma00185 Italy Dipartimento di Fisica dell’Università La Sapienza P.le Aldo Moro 2 Roma00185 Italy LPHEA Faculty of Science - Semlali Cadi Ayyad University MarrakechP.O.B. 2390 Morocco INFN - Sezione di Bari Via E. Orabona 4 Bari70126 Italy Department of Computer Architecture and Technology CITIC University of Granada Granada18071 Spain Université Paris-Sud Orsay Cedex91405 France Laboratoire de Physique Corpusculaire Clermont Université Université Blaise Pascal

Searches for dark matter (DM) have not provided any solid evidence for the existence of weakly interacting massive particles in the GeV-TeV mass range. Coincidentally, the scale of new physics is being pushed by collider searches well beyond the TeV domain. This situation strongly motivates the exploration of DM masses much larger than a TeV. Secluded scenarios contain a natural way around the unitarity bound on the DM mass, via the early matter domination induced by the mediator of its interactions with the Standard Model. High-energy neutrinos constitute one of the very few direct accesses to energy scales above a few TeV. An indirect search for secluded DM signals has been performed with the ANTARES neutrino telescope using data from 2007 to 2015. Upper limits on the DM annihilation cross section for DM masses up to 6 PeV are presented and discussed. © 2022, CC0.

关键词： Galaxies

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Embedded Software of the KM3NeT Central Logic Board

arXiv

引用

arXiv 2023年

作者： Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, E. Anghinolfi, M. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. Bagatelas, C. Bailly-Salins, L. Bardačová, Z. Baret, B. du Pree, S. Basegmez Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Benoit, D.M. Berbee, E. Bertin, V. van Beveren, V. Biagi, S. Boettcher, M. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Decoene, V. Del Burgo, R. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Fusco, L.A. Gabella, O. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Girardi, A. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, B. Gutiérrez, M. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. Jansweijer, P. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. Lastoria, C. Lazo, A. Le Stum, S. Lehaut, G. Leonora, E. INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France IFIC - Instituto de Física Corpuscular CSIC - Universitat de València c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ. CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy University of Granada Dept. of Computer Architecture and Technology CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP 20722 Nantes44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ. ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia National Institute for Subatomic Physics PO Box 41882 Amsterdam1009 DB Netherlands INFN Sezione di Bologna

The KM3NeT Collaboration is building and operating two deep sea neutrino telescopes at the bottom of the Mediterranean Sea. The telescopes consist of latices of photomultiplier tubes housed in pressure-resistant glass spheres, called digital optical modules and arranged in vertical detection units. The two main scientific goals are the determination of the neutrino mass ordering and the discovery and observation of high-energy neutrino sources in the Universe. Neutrinos are detected via the Cherenkov light, which is induced by charged particles originated in neutrino interactions. The photomultiplier tubes convert the Cherenkov light into electrical signals that are acquired and timestamped by the acquisition electronics. Each optical module houses the acquisition electronics for collecting and timestamping the photomultiplier signals with one nanosecond accuracy. Once finished, the two telescopes will have installed more than six thousand optical acquisition nodes, completing one of the more complex networks in the world in terms of operation and synchronization. The embedded software running in the acquisition nodes has been designed to provide a framework that will operate with different hardware versions and functionalities. The hardware will not be accessible once in operation, which complicates the embedded software architecture. The embedded software provides a set of tools to facilitate remote manageability of the deployed hardware, including safe reconfiguration of the firmware. This paper presents the architecture and the techniques, methods and implementation of the embedded software running in the acquisition nodes of the KM3NeT neutrino telescopes. © 2023, CC BY-NC-ND.

关键词： Photomultipliers

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GROUP-WISE SPARSE REPRESENTATION OF RESTING-STATE FMRI DATA FOR BETTER UNDERSTANDING OF SCHIZOPHRENIA

GROUP-WISE SPARSE REPRESENTATION OF RESTING-STATE FMRI DATA ...

引用

International Symposium on Biomedical Imaging

作者： Lin Yuan Tianming Liu Dewen Hu College of Mechanotrics and Automation National University of Defense Technology Changsha Hunan 410073 China Cortical Architecture Imaging and Discovery Lab Department of Computer Science The University of Georgia Athens United States of America

ISBN: (纸本)9781509011735

Resting-state functional magnetic resonance imaging (rs-fMRI) has become a powerful technique for analyzing cognitive function and its disruption in mental diseases, including schizophrenia. It has played an important role in analyzing and diagnosing mental diseases. In this paper, we present a novel machine learning approach called group-wise sparse representation of rs-fMRI signals to find differences between schizophrenia patients and healthy controls. Firstly, we extract the fMRI signals from all subjects that are registered into the MNI atlas space in the pre-processing step to build a large input signal matrix. Secondly, we use online dictionary learning and sparse coding methods to derive the coefficient matrix. Thirdly, we use two-sample t-test to analyze the regions of increased and decreased activity in schizophrenia patients compared to healthy controls. Finally, by using the AAL atlas the distributions of the detected regions are obtained. We test our approach on the COBRE dataset and the experimental results show that the schizophrenia patients have increased activities mainly at the fronto-parietal network. All other networks excluding the fronto-parietal network show decreased phenomenon. These results provide novel insights into better understanding of schizophrenia.

关键词： resting-state fMRI group-wise sparse representation schizophrenia research

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Corrigendum to ‘Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling’ [Urban Climate 28 (2019) 100459]

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Urban Climate 2019年 30卷

作者： Jason Ching Dan Aliaga Gerald Mills Valery Masson Linda See Marina Neophytou Ariane Middel Alexander Baklanov Chao Ren Ed Ng Jimmy Fung Michael Wong Yuan Huang Alberto Martilli Oscar Brousse Iain Stewart Xiaowei Zhang Aly Shehata Dev Niyogi Institute for the EnvironmentUNC at Chapel HillNC United States Department of Computer Sciences Purdue UW Lafayette IN United States School of Geography University College of Dublin Dublin Ireland Meteo France Toulouse France IIASA Laxemburg Austria Civil and Environmental Engineering U of Cyprus Nicosia Cyprus Arizona State U Tempe AZ United States World Meteorology Office Geneva Switzerland Hong Kong U Hong Kong Department of Architecture CUHK Hong Kong Hong Kong Science and Technology U Hong Kong Department of Architecture SW Jiatong U Chengdu China CIEMAT Madrid ES Spain Dept Earth Environmental Science KU Leuven Leuven Belgium University of Toronto Canada Department of Computer Sciences Purdue U W. Lafayette IN United States DEAPS Purdue U. West Lafayette Indiana United States

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引用

作者： Mori, Usue Mendiburu, Alexander Lozano, Jose A. Department of Computer Science and Artificial Intelligence University of the Basque Country UPV/EHU Gipuzkoa20018 Spain Department of Computer Architecture and Technology University of the Basque Country UPV/EHU Gipuzkoa20018 Spain

In the past few years, clustering has become a popular task associated with time series. The choice of a suitable distance measure is crucial to the clustering process and, given the vast number of distance measures for time series available in the literature and their diverse characteristics, this selection is not straightforward. With the objective of simplifying this task, we propose a multi-label classification framework that provides the means to automatically select the most suitable distance measures for clustering a time series database. This classifier is based on a novel collection of characteristics that describe the main features of the time series databases and provide the predictive information necessary to discriminate between a set of distance measures. In order to test the validity of this classifier, we conduct a complete set of experiments using both synthetic and real time series databases and a set of five common distance measures. The positive results obtained by the designed classification framework for various performance measures indicate that the proposed methodology is useful to simplify the process of distance selection in time series clustering tasks. © 2015 IEEE.

关键词： Time series

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Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing

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Procedia computer science 2017年 113卷 202-209页

作者： M. Ehatisham-ul-Haq Muhammad Awais Azam Usman Naeem Shafiq ur Rѐhman Asra Khalid Faculty of Telecom and Information Engineering University of Engineering and Technology Taxila Punjab Pakistan School of Architecture Computing and Engineering University of East London E16 2RD United Kingdom Department of Applied Physics and Electronics Umeå University SE-90187 Sweden Department of Computer Science COMSATS Institute of Information Technology Wah Campus Pakistan

Smartphones are ubiquitous devices that enable users to perform many of their routine tasks anytime and anywhere. With the advancement in information technology, smartphones are now equipped with sensing and networking capabilities that provide context-awareness for a wide range of applications. Due to ease of use and access, many users are using smartphones to store their private data, such as personal identifiers and bank account details. This type of sensitive data can be vulnerable if the device gets lost or stolen. The existing methods for securing mobile devices, including passwords, PINs and pattern locks are susceptible to many bouts such as smudge attacks. This paper proposes a novel framework to protect sensitive data on smartphones by identifying smartphone users based on their behavioral traits using smartphone embedded sensors. A series of experiments have been conducted for validating the proposed framework, which demonstrate its effectiveness.

关键词： Activity Recognition Behavioral Biometrics Continuous Sensing Mobile Device Security Data Privacy Mobile Sensing Ubiquitous Computing User Identification

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Design and testing tool for a safe monitoring system for neurodegenerative disorder patients 3

Design and testing tool for a safe monitoring system for neu...

引用

3rd International Conference on Advances in Computational Tools for Engineering Applications, ACTEA 2016

作者： Halabi, Nashaat El Achkar, Roger Daou, Roy Abi Zeid Hayek, Ali Borcsok, Josef Department of Computer and Communications Engineering Faculty of Engineering American University of Science and Technology Beirut Lebanon Department of Biomedical Technologies Faculty of Public Health Lebanese German University Sahel Alma Lebanon Department of Computer Architecture and System Programming Faculty of Electrical Engineering/Computer Science University of Kassel Kassel Germany

ISBN: (纸本)9781467385237

This paper aims to develop a sensor based monitoring and analyzing system for Neuro-Degenerative Disorder patients (NDD);this may consist on SpO2 sensor, Electrophysiological sensors, NIBP, Motion Capture sensors and Eye Monitoring sensor, taking into consideration an acceptable cost for the whole system. Recorded data will be sent to an embedded decision making unit where detection, analysis, classification, prediction and action control will occur. The sensors and the decision making unit will be implemented in a comfortable jacket that doesn't affect the patients' movements and that can be used by several patients with reduced sensor placement alterations. The decision that can be made is creating a stimulus to avoid falling in case of sudden stop while moving, initiating an alarm, sending a notification to a mobile phone application, and/or telemedicine monitoring features. Artificial Neural Networks will be used to classify and predict the abnormal cases where action should be taken, and since the sensors will be continuously recording, it is possible to achieve continuous learning for the ANN as a first phase. Initial models will be defined by testing normal behaviors and some known abnormal behaviors or symptoms related to the electrical activity and other characteristics of the heart, oxygen saturation level, eye activity and body motion. © 2016 IEEE.

关键词： Neural networks

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Effectiveness of GPS technology in monitoring of traffic-induced response of highway steel bridge

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IOP Conference Series: Materials science and Engineering 2018年第1期419卷

作者： Piotr Górski Peter Breuer Eduard Konopka Monika Napieraj Opole University of Technology Faculty of Civil Engineering and Architecture Katowicka 48 Opole 45-061 Poland Stuttgart University of Applied Sciences Department of Geomatics Computer Science and Mathematics Schellingstraβe 24 Stuttgart 70174 Germany

Despite some disadvantages, regarding the limited accuracy, the Global Positioning System (GPS) is widely used in monitoring of long-span bridges. This paper is concerned with the analysis of the capabilities and limitations of the use of the GPS technology in monitoring of semi-static and dynamic vertical responses of a highway steel cable-stayed bridge excited by traffic loads. The field test was conducted on the Maxau Rhine Bridge, located over the Rhine River near Karlsruhe, Germany. The so-called baseline method with the Post-Processing mode was applied using two units Leica Viva GS15. The basic characteristics of the GPS background noise before and after filtering were examined in the time and frequency domain. The natural frequencies of the bridge were extracted based on the vertical dynamic displacements recorded in the mid-span of the bridge using GPS and accelerometer. It was shown that the GPS receivers were able to measure only two primary modal frequencies of the bridge. The obtained experimental results proved that the GPS system is an efficient tool in measuring the vertical semi-static displacements of the bridge with satisfactory accuracy. Moreover, GPS is capable of tracking the vertical vibrations of long-period bridges to a few millimeters.

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First observation of the cosmic ray shadow of the Moon and the Sun with KM3NeT/ORCA

arXiv

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arXiv 2022年

作者： Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Anghinolfi, M. Anguita, M. Ardid, M. Ardid, S. Aublin, J. Bagatelas, C. Bailly-Salins, L. Baret, B. Basegmez du Pree, S. Becherini, Y. Bendahman, M. Benfenati, F. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bou Cabo, M. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Brânzaş, H. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Castaldi, P. Celli, S. Cerisy, L. Chabab, M. Chau, N. Chen, A. Cherkaoui El Moursli, R. Cherubini, S. Chiarella, V. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Del Burgo, R. Di Palma, I. Dìaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Eberl, T. Eddyamoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Espinosa, V. Ferrara, G. Filipović, M.D. Filippini, F. Fusco, L.A. Gabriel, J. Gal, T. García Méndez, J. Garcia Soto, A. Garufi, F. Gatius Oliver, C. Geißelbrecht, N. Gialanella, L. Giorgio, E. Girardi, A. Goos, I. Gozzini, S.R. Gracia, R. Graf, K. Guderian, D. Guidi, C. Guillon, B. Gutiérrez, M. Haegel, L. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. Janezashvili, D. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Kistauri, G. van der Knaap, F. Kooijman, P. Kouchner, A. Kulikovskiy, V. Labalme, M. Lahmann, R. Lakhal, A. Lamoureux, M. Larosa, G. Lastoria, C. Lazo, A. Le Breton, R. Le Stum, S. Lehaut, G. Leonora, E. Lessing, N. Levi, G. Liang, S. Lindsey Clark, M. Longhitano, F. Maderer, L. Majumdar, J. Mańczak, J. Margiotta, A. Marinelli, A. Markou, C. Martin, L. INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France IFIC - Instituto de Física Corpuscular CSIC - Universitat de València c/Catedrático José Beltrán 2 Valencia Paterna46980 Spain Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d'Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy University of Granada Dept. of Computer Architecture and Technology CITIC Granada18071 Spain Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/Paranimf 1 Gandia46730 Spain Université de Paris CNRS Astroparticule et Cosmologie ParisF-75013 France NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece LPC CAEN A02182036 6 boulevard Maréchal Juin Caen14050 France Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1009 DB Netherlands University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Pichat 6/2 Bologna40127 Italy INFN Laboratori Nazionali del Sud Via S. Sofia 62 Catania95123 Italy North-West University Centre for Space Research Private Bag X6001 Potchefstroom2520 South Africa Instituto Español de Oceanografía Unidad Mixta IEO-UPV C/Paranimf 1 Gandia46730

This article reports the first observation of the Moon and the Sun shadows in the sky distribution of cosmic-ray induced muons measured by the KM3NeT/ORCA detector. The analysed data-taking period spans from February 2020 to November 2021, when the detector had 6 Detection Units deployed at the bottom of the Mediterranean Sea, each composed of 18 Digital Optical Modules. The shadows induced by the Moon and the Sun were detected at their nominal position with a statistical significance of 4.2σ and 6.2σ, and an angular resolution of σres = 0.49◦ and σres = 0.66◦, respectively, consistent with the prediction of 0.53◦ from simulations. This early result confirms the effectiveness of the detector calibration, in time, position and orientation and the accuracy of the event direction reconstruction. This also demonstrates the performance and the competitiveness of the detector in terms of pointing accuracy and angular resolution. Copyright © 2022, The Authors. All rights reserved.

关键词： Moon

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