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arXiv 2022年

作者： Chen, Zhihao Chen, Yu Wu, Yaodong Zhou, Xinxing Sun, Handong Low, Tony Chen, Hongsheng Lin, Xiao Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control Ministry of Education Synergetic Innovation Center for Quantum Effects and Applications School of Physics and Electronics Hunan Normal University Changsha410081 China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong Province Institute of Microscale Optoelectronics Shenzhen University Shenzhen518060 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining314400 China

Photonic spin Hall effect is a manifestation of spin-orbit interaction of light and can be measured by a transverse shift δ of photons with opposite spins. The precise measurement of transverse shifts can enable many spin-related applications, such as precise metrology and optical sensing. However, this transverse shift is generally small (i.e. δ/λ -1, λ is the wavelength), which impedes its precise measurement. To-date proposals to generate giant spin Hall effect (namely with δ/λ > 102) have severe limitations, particularly its occurrence only over a narrow angular cone (with a width of ∆0 70◦ by exploiting the interface between free space and uniaxial epsilon-near-zero media. The underlying mechanism is ascribed to the almost-perfect polarization splitting between s and p polarized waves at the designed interface. Remarkably, this almost-perfect polarization splitting does not resort to the interference effect and is insensitive to the incident angle, which then gives rise to the wide-angle giant photonic spin Hall effect. Copyright © 2022, The Authors. All rights reserved.

关键词： Polarization

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Designing a Trajectory control System for Wheelchairs with a Combination of automatic and Manual Steering Methods

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Periodica Polytechnica Transportation engineering 2024年第4期52卷 412-422页

作者： Vu, Van Tan Nguyen, Quang Thinh Nakagawa, Chihiro Nguyen, Trung Nguyen Le, Thanh Long Nguyen, Van Vinh Hoang, Thi Lan Anh Do, Trong Tu Mihály, András Gáspár, Péter Department of Automotive Mechanical Engineering Faculty of Mechanical Engineering University of Transport and Communications Building A6 no. 3 Cau Giay Street Lang Thuong Ward Dong Da District Hanoi100000 Viet Nam Japan Technology Solution Joint Stock Company 9 Dau Ma Street Section 2 Thi Cau Ward Bac Ninh Bac Ninh222000 Viet Nam School of Engineering Osaka Metropolitan University 1-1 Gakuen-cho Nakaku Sakai Osaka599-8531 Japan Emergency abdominal surgery Department Viet Duc University Hospital no. 40 Trang Thi Street Hanoi100000 Viet Nam Mechanical and Power Engineering Faculty Electric Power University no. 235 Hoang Quoc Viet Street Co Nhue Ward Bac Tu Liem District Hanoi100000 Viet Nam Systems and Control Laboratory Institute for Computer Science and Control Hungarian Research Network Kende u. 13-17 Budapest1111 Hungary

A wheelchair is a specialized form of Personal Mobility Vehicle (PMV) designed to help people with disabilities move safely to their desired locations. Unlike conventional PMVs, wheelchairs for people with disabilities are challenging to manually control in environments with heavy traffic. This study focuses on designing and feasibility testing of control systems for PMVs to meet safety and efficiency standards, even in complex environments. First, a control structure model for PMVs is proposed. This is followed by the application of a combination of First In First Out (FIFO) and Dijkstra traffic control methods to determine effective trajectories for PMVs. The proposed control system is then tested on the campus of the University of Transport and Communications. Simulation results show that when comparing the travel time of 10 PMVs, the order execution time for each PMV remains stable (within 10%) for up to 20 PMVs. However, when the number of PMVs increases to 25, 30, 35, and 40 vehicles, the order execution time increases by 35%, 55%, 103%, and 119%, respectively. These results demonstrate that the system can control a large number of PMVs, ensuring safety, flexibility, and efficiency. © 2024 Budapest University of technology and Economics. All rights reserved.

关键词： Travel time

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Robust medical instrument segmentation challenge 2019

arXiv

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arXiv 2020年

作者： Roβ, Tobias Reinke, Annika Full, Peter M. Wagner, Martin Kenngott, Hannes Apitz, Martin Hempe, Hellena Filimon, Diana Mindroc Scholz, Patrick Tran, Thuy Nuong Bruno, Pierangela Arbelaéz, Pablo Bian, Gui-Bin Bodenstedt, Sebastian Bolmgren, Jon Lindström Bravo-Sánchez, Laura Chen, Hua-Bin González, Cristina Guo, Dong Halvorsen, Pål Heng, Pheng-Ann Hosgor, Enes Hou, Zeng-Guang Isensee, Fabian Jha, Debesh Jiang, Tingting Kirtac, Kadir Jin, Yueming Kletz, Sabrina Leger, Stefan Li, Zhixuan Maier-Hein, Klaus H. Ni, Zhen-Liang Riegler, Michael A. Schoeffmann, Klaus Shi, Ruohua Speidel, Stefanie Stenze, Michael Twick, Isabell Wang, Gutai Wang, Jiacheng Wang, Liansheng Wang, Lu Zhang, Yujie Zhou, Yan-Jie Zhu, Lei Wiesenfarth, Manuel Kopp-Schneider, Annette Müller-Stich, Beat P. Maier-Hein, Lena Heidelberg Germany University of Heidelberg Germany Heidelberg Germany Department of General Heidelberg University Hospital Visceral and Transplant Surgery Heidelberg Germany caresyntax Berlin Germany University of Chinese Academy Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China SimulaMet Oslo Norway Tromsø Norway Oslo Norway School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Partner Site Dresden Heidelberg Germany Faculty of Medicine and University Hospital Carl Gustav Carus Technische Universität Dresden Dresden Germany Dresden Germany Universidad de Los Andes Bogotá Colombia Peking University Peking China Department of Computer Science School of Informatics Xiamen University Xiamen China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong German Cancer Research Center Division of Biostatistics Heidelberg Germany Institute of Information Technology Klagenfurt University Austria

Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and roboticassisted interventions. While numerous methods for detecting, segmenting and tracking of medical instruments based on endoscopic video images have been proposed in the literature, key limitations remain to be addressed: Firstly, robustness, that is, the reliable performance of state-of-the-art methods when run on challenging images (e.g. in the presence of blood, smoke or motion artifacts). Secondly, generalization;algorithms trained for a specific intervention in a specific hospital should generalize to other interventions or institutions. In an effort to promote solutions for these limitations, we organized the Robust Medical Instrument Segmentation (ROBUST-MIS) challenge as an international benchmarking competition with a specific focus on the robustness and generalization capabilities of algorithms. For the first time in the field of endoscopic image processing, our challenge included a task on binary segmentation and also addressed multi-instance detection and segmentation. The challenge was based on a surgical data set comprising 10,040 annotated images acquired from a total of 30 surgical procedures from three different types of surgery. The validation of the competing methods for the three tasks (binary segmentation, multi-instance detection and multi-instance segmentation) was performed in three different stages with an increasing domain gap between the training and the test data. The results confirm the initial hypothesis, namely that algorithm performance degrades with an increasing domain gap. While the average detection and segmentation quality of the best-performing algorithms is high, future research should concentrate on detection and segmentation of small, crossing, moving and transparent instrument(s) (parts). Copyright © 2020, The Authors. All rights reserved.

关键词： Endoscopy

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Corrigendum to “Mobile Target Tracking Based on Hybrid Open-Loop Monocular Vision Motion control Strategy”

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Discrete Dynamics in Nature and Society 2016年第1期2016卷

作者： Cao Yuan Ma Lianchuan Weigang Ma National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing 100044 *** School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044 *** State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 *** Faculty of Computer Science and Engineering Xi’an University of Technology Xi’an 710048 ***

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Efficient MedSAMs: Segment Anything in Medical Images on Laptop

arXiv

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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Magnetic swirls and associated fast magnetoacoustic kink waves in a solar chromospheric flux tube

arXiv

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arXiv 2017年

作者： Murawski, K. Kayshap, P. Srivastava, A.K. Pascoe, D.J. Jelínek, P. Kuźma, B. Fedun, V. Maria Curie-Sklodowska University Institute of Physics Group of Astrophysics Radziszewskiego 10 LublinPL–20 031 Poland Centre for Fusion Space and Astrophysics Department of Physics University of Warwick CV4 7AL United Kingdom Department of Physics Indian Institute of Technology Banaras Hindu University Varanasi221005 India University of South Bohemia Faculty of Science Institute of Physics and Biophysics Branišovská 1760 České BudějoviceCZ – 370 05 Czech Republic Space Systems Laboratory Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom

We perform numerical simulations of impulsively generated magnetic swirls in an isolated flux tube which is rooted in the solar photosphere. These swirls are triggered by an initial pulse in a horizontal component of the velocity. The initial pulse is launched either: (a) centrally, within the localized magnetic flux tube;or (b) off-central, in the ambient medium. The evolution and dynamics of the flux tube is described by three-dimensional, ideal magnetohydrodynamic equations. These equations are numerically solved to reveal that in case (a) dipole-like swirls associated with the fast magnetoacoustic kink and m = 1 Alfvén waves are generated. In case (b), the fast magnetoacoustic kink and m = 0 Alfvén modes are excited. In both these cases, the excited fast magnetoacoustic kink and Alfvén waves consist of similar flow pattern and magnetic shells are also generated with clockwise and counter-clockwise rotating plasma within them, which can be the proxy of dipole-shaped chromospheric swirls. The complex dynamics of vortices and wave perturbations reveals the channelling of sufficient amount of energy to fulfill energy losses in the chromosphere (∼ 104 W m−1) and in the corona (∼ 102 W m−1). Some of these numerical findings are reminiscent of signatures in recent observational data. Copyright © 2017, The Authors. All rights reserved.

关键词： Magnetic flux

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Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

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Nature Ecology & Evolution 2025年 1-12页

作者： Stephen Pringle Jessica C. Fisher Gail E. Austen Jake E. Bicknell Nicolas J. Deere Mohammad S. Farhadinia Charlie J. Gardner Richard A. Griffiths Daniel J. Ingram Matthew J. Struebig Natalie Yoh Zoe G. Davies Martin Dallimer Mark A. Goddard Katherine C. R. Baldock Miranda T. Prendergast-Miller Léni K. Le Goff Emma Hart Simón C. Smith Simon J. Langdale Sara-Adela Abad Marc Ancrenaz Fabio Angeoletto Fernando Auat Cheein Joseph J. Bailey Lindsay F. Banin Cristina Banks-Leite Aliyu S. Barau Reshu Bashyal Adam J. Bates Jon Bielby Serge Wich Christopher D. Williams Petra Bosilj Marc Hanheide Emma R. Bush Simon J. Butler Dan Carpenter Christopher F. Clements Antoine Cully Kendi F. Davies Brett A. Melbourne Michael Dodd Rosie Drinkwater Don A. Driscoll Guillaume Dutilleux Mads Dyrmann David P. Edwards Aisyah Faruk Richard Field Franziska Schrodt Robert J. Fletcher Chris W. Foster Richard Fox Richard M. Francksen Aldina M. A. Franco Alison M. Gainsbury Ioanna Giorgi Giovanni L. Masala Salua Hamaza Matt W. Hayward Marcus Hedblom Thorunn Helgason Sui P. Heon Kevin A. Hughes Edmund R. Hunt 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 Lindsay C. Maskell Eleni Matechou Barbara Mazzolai Alistair McConnell Aslan Miriyev Eric Djomo Nana Alessandro Ossola Sarah Papworth Catherine L. Parr Ana Payo-Payo Gad Perry Nathalie Pettorelli Marcus Rowcliffe Rajeev Pillay Simon G. Potts Lan Qie Carl D. Soulsbury Persie Rolley-Parnell Stephen J. Rossiter Heather Rumble Jon P. Sadler Christopher J. Sandom Asiem Sanyal Sarab S. Sethi Adi Shabrani Robert Siddall Robbert P. H. Snep Margaret C. Stanley Philip A. Stephens P. J. Stephenson Matthew Studley Martin Svátek Gilbert Tang Nicholas K. Taylor Kate D. L. Umbers Robert J. Ward Patrick J. C. White Mark J. Whittingham Ibrahim B. Yakubu Syed A. R. Zaidi Anna Zmarz Joeri A. Zwerts Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury 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 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 Milton Keynes UK Palaeogenomics Group Faculty of Veterinary Medicine Ludwig Maximilian University Munich Munich Germany School of Life and Environmental Sciences

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.

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Retraction Note: CanarDeep: a hybrid deep neural model with mixed fusion for rumour detection in social data streams

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Neural Computing and Applications 2024年第18期36卷 11073-11073页

作者： Jain, Deepak Kumar Kumar, Akshi Shrivastava, Akshat Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing China Department of Information Technology Netaji Subhas University of Technology Delhi India Department of Computer Science & Engineering Delhi Technological University Delhi India

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Developing a prototype concurrent design tool for composite topside structures

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NAVAL ENGINEERS JOURNAL 1997年第3期109卷 279-290页

作者： Dirlik, S Hambric, S Azarm, S Marquardt, M Hellman, A Bartlett, S Castelli, V Steve Dirlik:began his career at the Naval Surface Warfare Center Carderock Division in 1981 as an aerospace engineer co-op student. He completed his bachelor of science degree in aeropace and ocean engineering from Virginia Polytechnic Institute and State University in 1985 and his master of science degree in aerospace engineering from the University of Maryland in 1990. Mr. Dirlik recently completed a master of science program in applied physics at The Johns Hopins University and currently works in the Radar Cross Section and Target Physics Branch of the Signatures Directorate at the Naval Surface Warfare Center Corderoke Division. He has worked on Navy low observable programs since 1990. Stephen Hambric:is a research associate at the Applied Research Laboratory at The Pennsylvania State University. He received his B. S. and M.S. degree in mechanical engineering from Virginia Polytechnic Institute and State University and his D. Sc. in mechnical engineering from the George Washington University. He has worked on several computer aided multidiscikplinary design and optimization projects over the years including an automated propeller design system and a structural acoustic optimization capability. Dr. Shpour Azarm:is currently working as an associate professor with the Design and Manufacturing Group of the Department of Mechanical Engineering at the University of maryland at College Park. Dr Azarm's expertise is in the areas of optimization-based designed and concurrent design and optimization of multidisciplinary systems. He was a consultant at Black & Decker Corporation (summer 1996) and worked as a Navy senior summer faculty fellow (summer 1995) and a NASA summer faculty fellow (summer 1994). He was a visiting scientist at NASA Langley Research Center for Multidisciplinary Analysis and Applied Structural Optimzatiom at the University of Siegen in Germany (spring 1992) and the Design Institute of the Technical University of Denmark (summer 1990). Dr Azarm was an associate technical editor of the ASME Jour

A prototype concurrent engineering tool has been developed for the preliminary design of composite topside structures for modern navy warships. This tool, named GELS for the Concurrent engineering of Layered Structures, provides designers with an immediate assessment of the impacts of their decisions on several disciplines which are important to the performance of a modern naval topside structure, including electromagnetic interference effects (EMI), radar cross section (RCS), structural integrity, cost, and weight. Preliminary analysis modules in each of these disciplines are integrated to operate from a common set of design variables and a common materials database. Performance in each discipline and an overall fitness function for the concept are then evaluated. A graphical user interface (GUI) is used to define requirements and to display the results from the technical analysis modules. Optimization techniques, including feasible sequential quadratic programming (FSQP) and exhaustive search are used to modify the design variables to satisfy all requirements simultaneously. The development of this tool, the technical modules, and their integration are discussed noting the decisions and compromises required to develop and integrate the modules into a prototype conceptual design tool.

关键词： Warships

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Corrigendum to “Analysis of optical properties and geometrical factors of linear deflection surface concentrators” [Sol. Energy Mater. Sol. Cells 121 (2014) 53–60]

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Solar Energy Materials and Solar Cells 2015年 132卷 319-319页

作者： Rao Kuang Yun Wu Jing Zheng Chaofeng Ye Xiyan Zhang Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and Environment Southeast University Nanjing 210096 China College of Civil Engineering Hunan University Changsha 410082 China School of Computer Science & Technology Soochow University Soochow 215003 China

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