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Advances in Intelligent Systems and Computing 2021年 1175卷 iv-vi页

作者： Sharma, Neha Chakrabarti, Amlan Balas, Valentina Emilia Martinovic, Jan Society for Data Science PuneMaharashtra India Department of Automatics and Applied Software Faculty of Engineering University of Arad Arad Romania A.K. Choudhury School of Information Technology University of Calcutta KolkataWest Bengal India IT4Innovations VSB-Technical University of Ostrava Ostrava Czech Republic

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The PLATO mission

引用

Experimental Astronomy 2025年第3期59卷 1-111页

作者： Rauer, Heike Aerts, Conny Cabrera, Juan Deleuil, Magali Erikson, Anders Gizon, Laurent Goupil, Mariejo Heras, Ana Walloschek, Thomas Lorenzo-Alvarez, Jose Marliani, Filippo Martin-Garcia, César Mas-Hesse, J. Miguel O’Rourke, Laurence Osborn, Hugh Pagano, Isabella Piotto, Giampaolo Pollacco, Don Ragazzoni, Roberto Ramsay, Gavin Udry, Stéphane Appourchaux, Thierry Benz, Willy Brandeker, Alexis Güdel, Manuel Janot-Pacheco, Eduardo Kabath, Petr Kjeldsen, Hans Min, Michiel Santos, Nuno Smith, Alexis Suarez, Juan-Carlos Werner, Stephanie C. Aboudan, Alessio Abreu, Manuel Acuña, Lorena Adams, Moritz Adibekyan, Vardan Affer, Laura Agneray, François Agnor, Craig Aguirre Børsen-Koch, Victor Ahmed, Saad Aigrain, Suzanne Al-Bahlawan, Ashraf Alcacera Gil, Ma de los Angeles Alei, Eleonora Alencar, Silvia Alexander, Richard Alfonso-Garzón, Julia Alibert, Yann Allende Prieto, Carlos Almeida, Leonardo Alonso Sobrino, Roi Altavilla, Giuseppe Althaus, Christian Alvarez Trujillo, Luis Alonso Amarsi, Anish Ammler-von Eiff, Matthias Amôres, Eduardo Andrade, Laerte Antoniadis-Karnavas, Alexandros António, Carlos Aparicio del Moral, Beatriz Appolloni, Matteo Arena, Claudio Armstrong, David Aroca Aliaga, Jose Asplund, Martin Audenaert, Jeroen Auricchio, Natalia Avelino, Pedro Baeke, Ann Baillié, Kevin Balado, Ana Ballber Balagueró, Pau Balestra, Andrea Ball, Warrick Ballans, Herve Ballot, Jerome Barban, Caroline Barbary, Gaële Barbieri, Mauro Barceló Forteza, Sebastià Barker, Adrian Barklem, Paul Barnes, Sydney Barrado Navascues, David Barragan, Oscar Baruteau, Clément Basu, Sarbani Baudin, Frederic Baumeister, Philipp Bayliss, Daniel Bazot, Michael Beck, Paul G. Belkacem, Kevin Bellinger, Earl Benatti, Serena Benomar, Othman Bérard, Diane Bergemann, Maria Bergomi, Maria Bernardo, Pierre Biazzo, Katia Bignamini, Andrea Bigot, Lionel Billot, Nicolas Binet, Martin Biondi, David Biondi, Federico Birch, Aaron C. Bitsch, Bertram Bluhm Ceballos, Paz Victoria Bódi, Attila Bognár, Zsófia Boisse, Isabelle Bolmont, Emeline Bonanno, Alfio Bonavita, Institut für Planetenforschung Deutsches Zentrum für Luft- und Raumfahrt DLR Rutherfordstrasse 2 Berlin 12489 Germany Fachbereich Geowissenschaften Institut für Geologische Freie Universität Berlin Malteserstr. 74-100 Berlin 12249 Germany Institute of Astronomy KU Leuven Leuven Belgium CNRS CNES LAM Aix Marseille University Marseille France Max Planck Institute for Solar System Research Göttingen Germany LESIA Paris Observatory PSL University Sorbonne University Paris Cité University CNRS Meudon France ESTEC European Space Agency Noordwijk Netherlands ESAC European Space Agency Madrid Spain Centro de Astrobiología CSIC-INTA Campus ESAC Madrid Spain Center for Space and Habitability University of Bern Bern Switzerland INAF - Osservatorio Astrofisico di Catania Catania Italy Department of Physics and Astronomy University of Padua Padua Italy Department of Physics University of Warwick Coventry United Kingdom Astronomical Observatory of Padova INAF - Italian National Institute for Astrophysics Padua Italy Armagh Observatory and Planetarium College Hill Armagh United Kingdom Geneve Observatory University of Geneve Geneve Switzerland IAS University of Paris-Saclay Orsay France AlbaNove University Centre Stockholm University Stockholm Sweden Department of Astrophysics University of Vienna Vienna Austria Department of Astronomy University of Sao Paulo Sao Paulo Brazil Astronomical Institute of the Czech Academy of Sciences Ondřejov Czech Republic Department of Physics and Astronomy Aarhus University Aarhus Denmark Institute for Space Research SRON Leiden Netherlands Instituto de Astrofísica e Ciências do Espaço CAUP Universidade do Porto Porto Portugal Departamento de Física e Astronomia Faculdade da Ci ncias Universidade do Porto Porto Portugal Mullard Space Science Laboratory University College London Holmbury Saint Mary United Kingdom Dept. Theoretical Physics and the Cosmos University of Granada Granada Spain Centre for Plan

PLATO (PLAnetary Transits and Oscillations of stars) is ESA’s M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2REarth) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5%, 10%, 10% for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO‘s target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile towards the end of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases. © The Author(s) 2025.

关键词： Asteroseismology Exoplanets PLATO mission

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FMPS of Master-Slave Dynamical Networks with Hybrid Feedback Control

FMPS of Master-Slave Dynamical Networks with Hybrid Feedback...

引用

International conference on applied Mathematics, Modeling and Computational science, AMMCS 2017

作者： Wang, Xin Liu, Xinzhi She, Kun Zhong, Shouming School of Information and Software Engineering University of Electronic Science and Technology of China ChengduSichuan610054 China Department of Applied Mathematical University of Waterloo WaterlooONN2L 3G1 Canada School of Mathematical Sciences University of Electronic Science and Technology of China ChengduSichuan611731 China

ISBN: (纸本)9783319997186

In this paper, the problem concerning function matrix projective synchronization (FMPS) for two different coupled complex dynamical networks with nonidentical nodes of different dimensions is investigated, in which the internal time delay is different from the coupling delay. With the aid of Lyapunov stability theory and mathematical induction, a hybrid feedback control protocol is proposed to achieve the FMPS. In contrast to most existing results, the symmetric or diffusive criteria for the coupling matrices are not needed. Numerical example is presented to illustrate the effectiveness and conservatism reduction of the proposed scheme. © 2018, Springer Nature Switzerland AG.

关键词： Complex networks

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An Improved Artificial Fish Swarm Algorithm and Its Application to Packing and Layout Problems 36

An Improved Artificial Fish Swarm Algorithm and Its Applicat...

引用

第36届中国控制会议

作者： Guangqiang Li Yawei Yang Tinglu Zhao Peixiang Peng Yiran Zhou Ying Hu Chen Guo School of Information Science and Technology Dalian Maritime University School of Software and Applied Technology Zhengzhou University

ISBN: (纸本)9781538629185

Packing and layout problems belong to NP-Complete problems theoretically and they occur extensively in many engineering fields in *** fish swarm algorithm（AFSA） is a newly proposed promising swarm intelligent optimization *** we try to apply this novel intelligent algorithm to solving packing and layout *** there still exist some defects of this algorithm itself,such as low convergence rate and precision,premature as well as poor ability of balancing exploitation and *** overcome them,an improved parallel adaptive hybrid artificial fish swarm algorithm（PAHAFSA） is *** algorithm divides the whole population into two subpopulations（groups） with the same size,and different adaptive strategies are applied to the two groups respectively to make one group focus on global search while the other on local *** two subpopulations evolve independently and individual migrations are conducted regularly to achieve information communication,increase the population diversity and improve convergence rate of proposed *** the information on the bulletin board does not change for a certain times,the hybrid strategy based on simulated annealing method will be introduced to help the algorithm escape from local optima and accelerate convergence *** example of packing and layout problems shows that PAHAFSA is feasible and effective.

关键词： Artificial fish swarm algorithm Parallel computation Adaptive Hybrid Layout

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Preface

Advances in Intelligent Systems and Computing

引用

Advances in Intelligent Systems and Computing 2021年 1174卷 v-vi页

作者： Sharma, Neha Balas, Valentina Emilia Chakrabarti, Amlan Martinovic, Jan Society for Data Science Pune Maharashtra India Department of Automatics and Applied Software Faculty of Engineering University of Arad Arad Romania A.K. Choudhury School of Information Technology West Bengal India Faculty of Engineering University of Calcutta Kolkata India IT4Innovations VSB-Technical University of Ostrava Ostrava Czech Republic

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First Results from the REAL-time Transient Acquisition backend (REALTA) at the Irish LOFAR station

arXiv

引用

arXiv 2021年

作者： Murphy, Pearse C. Callanan, P. McCauley, J. McKenna, D.J. Fionnagáin, D.Ó. Louis, C.K. Redman, M.P. Cañizares, L.A. Carley, E.P. Maloney, S.A. Coghlan, B. Daly, M. Scully, J. Dooley, J. Gajjar, V. Giese, C. Brennan, A. Keane, E.F. Maguire, C.A. Quinn, J. Mooney, S. Ryan, A.M. Walsh, J. Jackman, C.M. Golden, A. Ray, T.P. Doyle, J.G. Rigney, J. Burton, M. Gallagher, P.T. School of Physics Trinity College Dublin Dublin 2 Ireland Astronomy & Astrophysics Section Dublin Institute for Advanced Studies D02 XF86 Ireland Department of Physics University College Cork Cork Ireland Astrophysics Research Group School of Mathematics Statistics and Applied Mathematics National University of Ireland Galway University Road GalwayH91 TK33 Ireland Centre for Astronomy School of Physics National University of Ireland Galway University Road GalwayH91 TK33 Ireland School of Computer Science and Statistics Trinity College Dublin Dublin 2 Ireland Deptartment of Computer and Software Engineering Athlone Institute of Technology Athlone Ireland Department of Astronomy University of California BerkeleyCA94720 United States School of Physics University College Dublin Belfield Dublin 4 Ireland Armagh Observatory and Planetarium College Hill ArmaghBT61 9DG United Kingdom Astrophysics Research Centre School of Mathematics and Physics Queen's University Belfast BelfastBT7 1NN United Kingdom

Modern radio interferometers such as the LOw Frequency ARray (LOFAR) are capable of producing data at hundreds of gigabits to terabits per second. This high data rate makes the analysis of radio data cumbersome and computationally expensive. While high performance computing facilities exist for large national and international facilities, that may not be the case for instruments operated by a single institution or a small consortium. Data rates for next generation radio telescopes are set to eclipse those currently in operation, hence local processing of data will become all the more important. Here, we introduce the REAL-time Transient Acquisition backend (REALTA), a computing backend at the Irish LOFAR station (I-LOFAR) which facilitates the recording of data in near real-time and post-processing. We also present first searches and scientific results of a number of radio phenomena observed by I-LOFAR and REALTA, including pulsars, fast radio bursts (FRBs), rotating radio transients (RRATs), the search for extraterrestrial intelligence (SETI), Jupiter, and the Sun. © 2021, CC BY.

关键词： Interferometers

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An image segmentation framework for extracting tumors from breast magnetic resonance images

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Journal of Innovative Optical Health sciences 2018年第4期11卷 1-15页

作者： Le Sun Jinyuan He Xiaoxia Yin Yanchun Zhang Jeon-Hor Chen Tomas Kron Min-Ying Su School of Computer and Software Nanjing University of Information Science and Technology P.R.China Center for Applied Informatics Victoria University Australia Center for Functional Onco-Imaging of the Department of Radiological Sciences University of California Irvine USA Department of Radiology E-Da Hospital and I-Shou University KaohsiungTaiwan Peter MacCallum Cancer Centre Australia

Magnetic resonance imaging(MRI)has been a prevalence technique for breast cancer ***-aided detection and segmentation of lesions from MRIs plays a vital role for the MRI-based disease *** are two main issues of the existing breast lesion segmentation techniques:requir ing manual delineation of Regions of Interests(ROIs)as a step of initialization;and requiring a large amount of labeled images for model construction or parameter lear ning,while in real clinical or experimental settings,it is highly challenging to get suficient labeled *** resolve these issues,this work proposes a semi-supervised method for breast tumor segmentation based on super voxel *** image segmentation with advanced cluster techniques,we take a supervised learning step to classify the tumor and nontumor patches in order to automatically locate the tumor regions in an MRI To obtain the opt imal performance of tumor extraction,we take extensive experiments to learn par ameters for tumor segmentation and dassification,and design 225 classifiers corresponding to diferent parameter *** call the proposed method as Semi supervised Tumor Segmentation(SSTS),and apply it to both mass and nonmass *** results show better performance of SsTS compared with five state of-the art methods.

关键词： Breast lesion image segmentation MRI

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Designing transformation-induced plasticity and twinning-induced plasticity Cr-Co-Ni medium entropy alloys: Theory and experiment

arXiv

引用

arXiv 2020年

作者： Yang, Zhibiao Lu, Song Tian, Yanzhong Gu, Zijian Mao, Huahai Sun, Jian Vitos, Levente Shanghai Key Laboratory of Advanced High-Temperature Materials and Precision Forming School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Applied Materials Physics Department of Materials Science and Engineering Royal Institute of Technology StockholmSE-100 44 Sweden School of Materials Science and Engineering Northeastern University Shenyang110819 China Unit of Structures Dept Materials Science and Engineering KTH StockholmSE-10044 Sweden Thermo-Calc Software Råsundav. 18 SolnaSE-16767 Sweden Division of Materials Theory Department of Physics and Materials Science Uppsala University P.O. Box 516 UppsalaSE-75120 Sweden Research Institute for Solid State Physics and Optics Wigner Research Center for Physics P.O.Box 49 BudapestH-1525 Hungary

In order to efficiently explore the nearly infinite composition space in multicomponent solid solution alloys, it is important to establish predictive design strategies and use computation-aided methods. In the present work, we demonstrated the density functional theory calculations informed design routes for realizing transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP) in Cr-Co-Ni medium entropy alloys (MEAs). We systematically studied the effects of magnetism and chemical composition on the generalized stacking fault energy surface (γ-surface) and showed that both chemistry and the coupled magnetic state strongly affect the γ-surface, consequently, the primary deformation modes. Based on the calculated effective energy barriers for the competing deformation modes, we constructed composition and magnetism dependent deformation maps at both room and cryogenic temperatures. Accordingly, we proposed various design routes for achieving desired primary deformation modes in the ternary Cr-Co-Ni alloys. The deformation mechanisms predicted by our theoretical models are in nice agreement with available experimental observations in literature. Furthermore, we fabricated two non-equiatomic Cr-Co-Ni MEAs possessing the designed TWIP and TRIP effects, showing excellent combinations of tensile strength and ductility. Copyright © 2020, The Authors. All rights reserved.

关键词： Nickel alloys

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Designing Transformation-Induced Plasticity and Twinning-Induced Plasticity Cr-Co-Ni Medium Entropy Alloys: Theory and Experiment

SSRN

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SSRN 2020年

关键词： Nickel alloys

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Task-Oriented Convex Bilevel Optimization with Latent Feasibility

arXiv

引用

arXiv 2019年

作者： Liu, Risheng Ma, Long Yuan, Xiaoming Zeng, Shangzhi Zhang, Jin DUT-RU International School of Information Science & Engineering Dalian University of Technology Dalian116024 China The School of Software Technology Dalian University of Technology Dalian116024 China The Peng Cheng Laboratory Shenzhen518052 China The Department of Mathematics The University of Hong Kong Hong Kong The Department of Mathematics and Statistics University of Victoria Canada The Department of Mathematics SUSTech International Center for Mathematics Southern University of Science and Technology National Center for Applied Mathematics Shenzhen Shenzhen518055 China

This paper firstly proposes a convex bilevel optimization paradigm to formulate and optimize popular learning and vision problems in real-world scenarios. Different from conventional approaches, which directly design their iteration schemes based on given problem formulation, we introduce a task-oriented energy as our latent constraint which integrates richer task information. By explicitly re-characterizing the feasibility, we establish an efficient and flexible algorithmic framework to tackle convex models with both shrunken solution space and powerful auxiliary (based on domain knowledge and data distribution of the task). In theory, we present the convergence analysis of our latent feasibility re-characterization based numerical strategy. We also analyze the stability of the theoretical convergence under computational error perturbation. Extensive numerical experiments are conducted to verify our theoretical findings and evaluate the practical performance of our method on different applications. Copyright © 2019, The Authors. All rights reserved.

关键词： Convex optimization

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