检索结果-内蒙古大学图书馆

Communications biology 2024年第1期7卷 1632页

作者： Takumi Tomoi Yuka Yoshida Suguru Ohe Yukiko Kabeya Mitsuyasu Hasebe Tomohiro Morohoshi Takashi Murata Joe Sakamoto Yosuke Tamada Yasuhiro Kamei Innovation Department Center for Innovation Support Institute for Social Innovation and Cooperation Utsunomiya University Utsunomiya Japan. t-tomoi@rs.tus.ac.jp. School of Engineering Utsunomiya University Utsunomiya Japan. t-tomoi@rs.tus.ac.jp. Department of Applied Biological Science Tokyo University of Science Noda Japan. t-tomoi@rs.tus.ac.jp. Laboratory for Biothermology National Institute for Basic Biology Okazaki Japan. t-tomoi@rs.tus.ac.jp. Graduate School of Regional Development and Creativity Utsunomiya University Utsunomiya Japan. School of Engineering Utsunomiya University Utsunomiya Japan. Division of Evolutionary Biology National Institute for Basic Biology Okazaki Japan. Department of Basic Biology The Graduate University for Advanced Studies (SOKENDAI) Okazaki Japan. Department of Applied Bioscience Kanagawa Institute of Technology Atsugi Japan. Laboratory for Biothermology National Institute for Basic Biology Okazaki Japan. Biophotonics Research Group Exploratory Research Center on Life and Living Systems (ExCELLS) Okazaki Japan. School of Engineering Utsunomiya University Utsunomiya Japan. tamada@cc.utsunomiya-u.ac.jp. Graduate School of Regional Development and Creativity Utsunomiya University Utsunomiya Japan. tamada@cc.utsunomiya-u.ac.jp. Division of Evolutionary Biology National Institute for Basic Biology Okazaki Japan. tamada@cc.utsunomiya-u.ac.jp. Department of Basic Biology The Graduate University for Advanced Studies (SOKENDAI) Okazaki Japan. tamada@cc.utsunomiya-u.ac.jp. Center for Optical Research and Education (CORE) Utsunomiya University Utsunomiya Japan. tamada@cc.utsunomiya-u.ac.jp. Robotics Engineering and Agriculture-technology Laboratory (REAL) Utsunomiya University Utsunomiya Japan. tamada@cc.utsunomiya-u.ac.jp. Laboratory for Biothermology National Institute for Basic Biology Okazaki Japan. ykamei@nibb.ac.jp. Department of Basic Biology The Graduate University for Advanced Studies (SOKENDAI) Okazaki Japan. ykamei@nibb

来源：评论

学校读者我要写书评

暂无评论

New design techniques for globally convergent simultaneous localization and mapping: Analysis and implementation

引用

Workshop on Sensing and Control for Autonomous Vehicles: Applications to Land, Water and Air Vehicles, 2017

作者： Lourenço, Pedro Guerreiro, Bruno Batista, Pedro Oliveira, Paulo Silvestre, Carlos Laboratory for Robotics and Engineering Systems Institute for Systems and Robotics Lisbon Portugal Department of Electrical and Computer Engineering Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal Department of Mechanical Engineering Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China

ISBN: (纸本)9783319553719

This chapter presents an overview of algorithms deeply rooted in a sensor-based approach to the SLAM problem that provide global convergence guarantees and allow for the use of partially observable landmarks. The presented algorithms address the more usual range-and-bearing SLAM problem, either in 2-D using a LiDAR or in 3-D using an RGB-D camera, as well as the range-only and bearing-only SLAM problems. For each of these formulations a nonlinear system is designed, for which state and output transformations are considered together with augmented dynamics, in such a way that the underlying system structure can be regarded as linear time-varying for observability analysis and filter design purposes. This naturally allows for the design of Kalman filters with, at least, globally asymptotically stable error dynamics, for which several experimental and simulated trials are presented to highlight the performance and consistency of the obtained filters. © Springer International Publishing AG 2017.

关键词： Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

引用

Nature ecology & evolution 2025年 2025 May 22页

作者： Stephen Pringle Martin Dallimer Mark A Goddard Léni K Le Goff Emma Hart Simon J Langdale Jessica C Fisher Sara-Adela Abad Marc Ancrenaz Fabio Angeoletto Fernando Auat Cheein Gail E Austen Joseph J Bailey Katherine C R Baldock Lindsay F Banin Cristina Banks-Leite Aliyu S Barau Reshu Bashyal Adam J Bates Jake E Bicknell Jon Bielby Petra Bosilj Emma R Bush Simon J Butler Dan Carpenter Christopher F Clements Antoine Cully Kendi F Davies Nicolas J Deere Michael Dodd Rosie Drinkwater Don A Driscoll Guillaume Dutilleux Mads Dyrmann David P Edwards Mohammad S Farhadinia Aisyah Faruk Richard Field Robert J Fletcher Chris W Foster Richard Fox Richard M Francksen Aldina M A Franco Alison M Gainsbury Charlie J Gardner Ioanna Giorgi Richard A Griffiths Salua Hamaza Marc Hanheide Matt W Hayward Marcus Hedblom Thorunn Helgason Sui P Heon Kevin A Hughes Edmund R Hunt Daniel J Ingram George Jackson-Mills Kelly Jowett Timothy H Keitt Laura N Kloepper Stephanie Kramer-Schadt Jim Labisko Frédéric Labrosse Jenna Lawson Nicolas Lecomte Ricardo F de Lima Nick A Littlewood Harry H Marshall Giovanni L Masala Lindsay C Maskell Eleni Matechou Barbara Mazzolai Alistair McConnell Brett A Melbourne Aslan Miriyev Eric Djomo Nana Alessandro Ossola Sarah Papworth Catherine L Parr Ana Payo-Payo Gad Perry Nathalie Pettorelli Rajeev Pillay Simon G Potts Miranda T Prendergast-Miller Lan Qie Persie Rolley-Parnell Stephen J Rossiter Marcus Rowcliffe Heather Rumble Jon P Sadler Christopher J Sandom Asiem Sanyal Franziska Schrodt Sarab S Sethi Adi Shabrani Robert Siddall Simón C Smith Robbert P H Snep Carl D Soulsbury Margaret C Stanley Philip A Stephens P J Stephenson Matthew J Struebig Matthew Studley Martin Svátek Gilbert Tang Nicholas K Taylor Kate D L Umbers Robert J Ward Patrick J C White Mark J Whittingham Serge Wich Christopher D Williams Ibrahim B Yakubu Natalie Yoh Syed A R Zaidi Anna Zmarz Joeri A Zwerts Zoe G Davies Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury UK. s.pringle@kent.ac.uk. Centre for Environmental Policy Imperial College London London UK. Department of Geography and Environmental Sciences Northumbria University Newcastle upon Tyne UK. School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK. Synthotech Ltd Milner Court Hornbeam Square Harrogate UK. Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury UK. Mechanical Engineering Department University College London London UK. HUTAN SWD Kota Kinabalu Malaysia. Programa de Pós-Graduação em Gestão e Tecnologia Ambiental da Universidade Federal de Rondonópolis Rondonópolis Brasil. Department of Engineering Harper Adams University Newport UK. Applied Ecology Research Group School of Life Sciences Anglia Ruskin University Cambridge UK. Centre for Ecology and Hydrology Penicuik UK. Department of Life Sciences Imperial College London Silwood Park Campus Ascot UK. Department of Urban and Regional Planning Faculty of Earth and Environmental Sciences Bayero University Kano Nigeria. Greenhood Nepal Kathmandu Nepal. Animal Rural & Environmental Sciences Nottingham Trent University Nottinghamshire UK. School of Biological and Environmental Sciences Liverpool John Moores University Liverpool UK. Lincoln Centre for Autonomous Systems University of Lincoln Lincoln UK. Royal Botanic Garden Edinburgh Edinburgh UK. School of Biological Sciences University of East Anglia Norwich Research Park Norwich UK. Digital Ecology Limited Bristol UK. School of Biological Sciences University of Bristol Bristol UK. Department of Computing Imperial College London London UK. Department of Ecology and Evolutionary Biology University of Colorado Boulder CO USA. Faculty of Science Technology Engineering and Mathematics (STEM) The Open University Walton Hall Milt

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more 'difficult' taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Introduction

Advances in Industrial Control

引用

Advances in Industrial Control 2018年第9783319610207期 1-18页

作者： Orsag, Matko Korpela, Christopher Oh, Paul Bogdan, Stjepan Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Department of Electrical Engineering and Computer Science United States Military Academy West PointNY United States Department of Mechanical Engineering University of Nevada Las Vegas Las VegasNV United States

Aerial robotics has reached significant maturity in the last few years. Thus, the number of new unmanned aerial vehicles (UAV) and unmanned aerial systems (UAS), applications, and companies producing them has increased in a very important way. The number of publications and presentations in conferences has also experienced a large increase. Moreover, almost every day we can find articles, videos, and news in the general media related to drones. © Springer International Publishing AG 2018.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Convex Combination for Source Localization Using Received Signal Strength Measurements

Convex Combination for Source Localization Using Received Si...

引用

International Conference on Information Fusion

作者： Qi Wang Zhansheng Duan X. Rong Li Uwe D. Hanebeck Center for Information Engineering Science Research Xi'an Jiaotong University Xi'an Shaanxi China Department of Electrical Engineering University of New Orleans New Orleans LA U.S.A Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany

Source localization is of great importance for wireless sensor network applications. Locating emission sources using received signal strength (RSS) measurements is investigated in this paper. As RSS localization is a non-convex optimization problem, it is difficult to achieve global optima. Many optimization methods have been proposed to relax it to a convex optimization problem. Unlike these methods, we propose a convex combination scheme. By introducing a highly accurate linear approximation of a logarithmic function, the source location is represented by a convex combination of a set of virtual anchors. Then the original problem is relaxed to be a convex optimization problem of finding the optimal combination coefficients, which can be solved efficiently using constrained least squares. To obtain the virtual nodes, we construct parallel lines and use their intersections to form a convex polygon, which covers the source location with certain probability. The vertices of the polygon are taken as the virtual nodes. Numerical examples verify the performance of the proposed method in both localization accuracy and computational efficiency.

关键词： Optimization Position measurement Wireless communication Maximum likelihood estimation Robot sensing systems Wireless sensor networks Convex functions

来源：评论

学校读者我要写书评

暂无评论

Relaxed conditions for uniform complete observability and controllability of LTV systems with bounded realizations

引用

IFAC-PapersOnLine 2017年第1期50卷 3598-3605页

作者： Batista P. Petit N. Silvestre C. Oliveira P. Institute for Systems and Robotics Laboratory for Robotics and Engineering Systems Instituto Superior Técnico Universidade de Lisboa Portugal MINES ParisTech PSL Research University CAS – Centre automatique et systémes 60 bd St Michel Paris 75272 France Department of Electrical and Computer Engineering Faculty of Science and Technology of the University of Macau Macau Department of Mechanical Engineering Instituto Superior Técnico Universidade de Lisboa Portugal

Uniform complete observability and controllability are key concepts for the design of state observers and controllers for linear time-varying systems. While the definitions of these properties are simple, it is more often that not very difficult to show they hold for a particular system. This paper presents alternative simpler sufficient conditions. Examples are shown that illustrate the improvement over previous results, the fact that the new conditions are not necessary, and a practical application. © 2017

关键词： linear time-varying systems uniform complete controllability uniform complete observability

来源：评论

学校读者我要写书评

暂无评论

Editor-in-Chief

引用

IEEE Access 2024年 12卷 i-xi页

作者： Derek Abbott Sonia Aissa Anuradha Annaswamy Nirwan Ansari Jun Cai Kun-Shan Chen Yixin Chen J.-C. Chiao Ayman El-Baz Shaikh Fattah Hoay Gooi Maya Gokhale Chih-Lin Ⅰ Giuseppe Iannaccone Yumi Iwashita Bruce Jacob Abbas Jamalipour Bahram Javidi Weihua Jiang Okyay Kaynak Hulya Kirkici Germano Lambert-Torres Shengtao Li Michal Mrozowski Michele Nappi Dalma Novak Hugo Proença Yi Qian Zhihua Qu Susanto Rahardja Mehrdad Saif Ali Serpengüzel Peter H. Siegel Ashitey Trebi-Ollennu Daniela Tuninetti Ge Wang Keith A. Wear Andreas Weisshaar C. Patrick Yue Enrico Zio School of Electrical and Electronic Engineering University of Adelaide Adelaide SA Australia Institut National de la Recherche Scientifique (INRS) Québec City Canada Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Concordia University Montreal Canada Guilin University of Technology Guilin China Washington University St. Louis MO USA Southern Methodist University Dallas TX USA University of Louisville/Bioengineering Department Louisville KY USA Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Nanyang Technological University Jurong West Singapore Lawrence Livermore National Laboratory Livermore CA USA China Mobile Research Institute Beijing China University of Pisa Pisa Italy NASA-JPL California Institute of Technology Pasadena CA USA Florida Polytechnic University Lakeland FL USA The University of Sydney Sydney NSW Australia University of Connecticut Storrs CT USA Nagaoka University of Technology Nagaoka Niigata Japan Department of Electrical and Electronic Engineering Boğaziçi University Istanbul Turkey University of South Alabama Mobile AL USA Gnarus Institute Itajuba Brazil Xi’an Jiaotong University Xi’an China Gdansk University of Technology Gdansk Poland University of Salerno Fisciano Italy Octane Wireless Hanover MD USA University of Beira Interior Covilhã Portugal Department of Electrical and Computer Engineering University of NebraskaLincoln Lincoln NE USA University of Central Florida Orlando Florida USA Singapore Institute of Technology 10 Dover Dr Singapore Infocomm Technology Cluster 10 Dover Dr Singapore University of Windsor Windsor Canada Department of Physics Koç University Istanbul Turkey California Institute of Technology (CalTech) Pasadena California USA NASA-JPL Mobility and Robotics Systems S

来源：评论

学校读者我要写书评

暂无评论

Common Limitations of Image Processing Metrics: A Picture Story

arXiv

引用

arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs 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 Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg 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 Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal 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 Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom 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 Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Development of a deep drill system with integrated UV/Raman spectrometer for mars and Europa

Development of a deep drill system with integrated UV/Raman ...

引用

AIAA Space and Astronautics Forum and Exposition, 2018

作者： Mellerowicz, Boleslaw Zacny, Kris Paulsen, Gale Kim, Daniel Bailey, Jameil Ngo, Peter Wang, Alexander Huddleston, Robert Chow, Paul Ridilla, Albert Nguyen, Huey Eshelman, Evan Malaska, Michael Wagner, Greg Abbey, William Manatt, Kenneth Doloboff, Ivria Lane, Arthur Beegle, Luther Bhartia, Rohit Priscu, John Willis, Madelyne Honeybee Robotics Engineering Technology Group 398 W Washington Blvd Suite 200 PasadenaCA91103 United States Jet Propulsion Laboratory Planetary Chemistry and Astrobiology Group 4800 Oak Grove Dr PasadenaCA91109 United States Jet Propulsion Laboratory Planetary Ices Group 4800 Oak Grove Dr PasadenaCA91109 United States Jet Propulsion Laboratory Systems and Nanoscience Group 4800 Oak Grove Dr PasadenaCA91109 United States Jet Propulsion Laboratory JPL’s Science Division 4800 Oak Grove Dr PasadenaCA91109 United States Montana State University Department of Land Resources and Environmental Sciences 211 Montana Hall BozemanMT59717 United States

ISBN: (纸本)9781624105753

Planetary exploration has been limited to surface and near surface terrains. To learn about planets’ histories and signatures of past or present life, deep drilling is required. This paper presents the WATSON (Wireline Analysis Tool for Subsurface Observations of Northern ice sheets) Planetary Deep Drill (PDD), a prototype drill built under NASA’s PSTAR funding designed for penetration and in-situ analysis of the borehole down to 100’s of meters into Mars’ ice caps and/or Europa’s ice sheets. The drill will perform in-situ analysis of the borehole with its integrated spectrometer called WATSON instrument. Designed by JPL, it is a deep UV/Raman and fluorescence spectrometer that is based on the Mars2020 SHERLOC instrument and has the objective of determining the spatial distribution of organics including microbes in glacial ice. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Drills

来源：评论

学校读者我要写书评

暂无评论

Correction to: Editorial

引用

International Journal of Social robotics 2019年第6期15卷 1077-1077页

作者： Ge, Shuzhi Sam Wykowska, Agnieszka Khatib, Oussama Social Robotics Laboratory Smart Systems Institute Department of Electrical and Computer Engineering The National University of Singapore Singapore Singapore Institute for Future (IFF) Qingdao University Qingdao China Centre for Robotics UESTC Chengdu China Social Cognition in Human-Robot Interaction Istituto Italiano di Tecnologia Genoa Italy Artificial Intelligence Laboratory Department of Computer Science Stanford University Stanford USA

This is to inform you that the following sentence was inadvertently omitted from the final version

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：