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58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017

作者： Colomer, Joan Mas Bartoli, Nathalie Lefebvre, Thierry Dubreuil, Sylvain Martins, Joaquim R. R. A. Bénard, Emmanuel Morlier, Joseph System Design and Performance Evaluation Department ONERA - The French Aerospace Lab Toulouse France Department of Aerospace Engineering University of Michigan Ann ArborMI48109-2102 United States Department of Aerospace Vehicles Design and Control Université de Toulouse ISAE SUPAERO Toulouse France Université de Toulouse ISAE SUPAERO-CNRS-INSA-Mines Albi-UPS Toulouse France

ISBN: (数字)9781624104534

ISBN: (纸本)9781624104534

The developments presented in this paper take place in the context of a broader series of works carried out at ONERA and ISAE on multidisciplinary design optimization applied to a scaled flight demonstrator. The aim of this work is to develop an optimization process capable of sizing a scaled flight demonstrator in order to reproduce several behaviors encountered on its corresponding full size aircraft. Unlike the classical optimization problems found in aeronautics, whose objective functions are performance-related (e.g. mass and drag minimization), we aim to maximize the similarity between the scaled model and the full size aircraft. In the aforementioned context, the first part of this paper corresponds to the static aeroelastic similarity problem. However, the approach described herein is general enough to treat other optimization problems, including performance-related ones. The second part of this work deals with the dynamic aspects of the aeroelastic similarity. A benchmark case is presented where the structural properties of a given geometry are optimized in order to match the reference modal parameters (i.e., mode shapes and frequencies) of the GARTEUR SM-AG19 model. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Optimization

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Towards an intelligent reconfigurable BLDC motor controller: Commutation configuration and parameters detection

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AIP Conference Proceedings 2019年第1期2187卷

作者： Agus Mukhlisin Estiko Rijanto I. Nyoman Sutantra Muhammad Nur Yuniarto Agus Sigit Pramono 1Sepuluh Nopember Institute of Technology Department of Mechanical Engineering Surabaya Indonesia 2Research Center for Electrical Power and Mechatronics Indonesian Institute of Sciences LIPI Indonesia 3Design Laboratory Mechanical Eng. Dept. Institut Teknologi Sepuluh Nopember Surabaya Indonesia 4Sepuluh Nopember Institute of Technology Center of Automotive Control System IPTEK Surabaya Indonesia

One of the key components in an electric vehicle is brushless direct current (BLDC) motor controller. At present, it is difficult to match a self-made motor controller with several different BLDC motors available in the global market. One of the reasons is that the Hall sensors’ configuration is not well informed. Another reason is the motor parameter’s values used in the controller are not well suited with the real physical conditions of the motor. This study aims to design an intelligent reconfigurable BLDC motor controller. In this paper, a method for automatic commutation configuration and automatic parameter values detection is presented. The Hall sensors and motor phases configurations are identified. The BLDC motor parameter values are detected automatically using mathematical models. Those parameters include internal resistance, inductance, coefficient of back electromotive force (BEMF), torque coefficient, friction coefficient, and moment of inertia. Experimental results of the automatic commutation configuration and parameter values detection are presented. Those results were used to develop a current controller. Further experimental results indicated that the method could be implemented in a BLDC motor current controller.

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Demo Abstract: Observability-driven sensor deployment in smart academic environments 14

Demo Abstract: Observability-driven sensor deployment in sma...

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14th ACM Conference on Embedded Networked Sensor systems, SenSys 2016

作者： Agarwal, A. Jaiswal, K. Gudhaka, U. Munigala, V. Ramamritham, Krithi Karmakar, Gopinath Department of Computer Science Engineering Indian Institute of Technology Bombay United States Reactor Control System Design Section Bhabha Atomic Research Centre India

ISBN: (纸本)9781450342636

Saving energy without causing discomfort and without de-manding human intervention is the need of the day. It is important to develop sensor systems which not only satisfy user requirements, but also take energy consumption into consideration. In this demo, we present the sensing subsys-tems of a Smart Academic Environment, based upon the core concept of Observability' [1] which-while satisfying user needs-helps to reduce the number of sensors required. © 2016 Copyright held by the owner/author(s).

关键词： Observability

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Finite Element Analysis on Loosen Teeth using Fibrous Periodontal Splint Restoration

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IOP Conference Series: Materials Science and engineering 2018年第1期417卷

作者： Chengshui Ding Xue Shi Yang Song Lulu Qiu Xinyue Li Chunqiu Zhang Tianjin Key Laboratory of the Design Intelligent Control of the Advanced Mechatronical System National Demonstration Center for Experimental Mechanical and Electrical Engineering Education School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China Periodontitis Department Tianjin Stomatological Hospital Tianjin 300384 China

Objective To investigate the effect of fibre periodontal splint restoration on mandibular anterior teeth displacement and periodontal membrane stress. Methods Micro-CT scanning technology, combined with Mimics, Geomagic studio and SolidWorks were used to establish 3D dental models of mandibles with teeth and the models fibre periodontal splint restoration; the models of mandibular anterior loosen teeth was constructed under 30 degree oblique 25N loading on the labial and lingual sides respectively. Then, under different angles force with or without the splint, the analysis on dental mechanical state are given. Results It was determined that the sum of the maximal displacement of the loosen tooth model at the lingual and labial sides was 1 mm, which represented the degree I loosen model. After splint repair on the model, the maximal displacement of loosen tooth decreased 47.7%, 85.1% and 85.8% at 0 degree, 15 degree and 30 degree forces respectively, and the maximum stress of periodontal membrane decreased by 22.3%, 61.2% and 74.9%. Conclusion Fixation of loosen teeth through fibre periodontal splints can reduce the maximum stress of periodontal membrane and the maximal displacement of the teeth, thus ensuring the stability of loosen tooth.

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration Automation

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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Observability-driven Sensor Deployment in Smart Academic Environments: Demo Abstract 16

Observability-driven Sensor Deployment in Smart Academic Env...

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Proceedings of the 14th ACM Conference on Embedded Network Sensor systems CD-ROM

作者： A. Agarwal K. Jaiswal U. Gudhaka V. Munigala Krithi Ramamritham Gopinath Karmakar Department of Computer Science & Engineering Indian Institute of Technology Bombay Reactor Control System Design Section Bhabha Atomic Research Centre

ISBN: (纸本)9781450342636

Saving energy without causing discomfort and without demanding human intervention is the need of the day. It is important to develop sensor systems which not only satisfy user requirements, but also take energy consumption into consideration. In this demo, we present the sensing subsystems of a Smart Academic Environment, based upon the core concept of 'Observability' [1] which -- while satisfying user needs -- helps to reduce the number of sensors required.

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Aerothermal design of the Hexafly-INT glider

Aerothermal design of the Hexafly-INT glider

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AIAA Space and Astronautics Forum and Exposition, SPACE 2016

作者： Scigliano, Roberto Pezzella, Giuseppe Marini, Marco Di Benedetto, Sara Steelant, Johan CIRA Italian Aerospace Research Center Thermal Structures and Thermal Control Technologies and Design Via Maiorise CapuaCE81043 Italy ESA-ESTEC European Space Agency Aerothermodynamics Analysis and extrapolation to Flight Lab Keplerlaan 1 Noordwijk2200 AZ Netherlands Space Department Technology Integration Aeronautics - System Engineering Netherlands

ISBN: (数字)9781624104275

ISBN: (纸本)9781624104275

Over the last years, innovative concepts of civil high-speed transportation vehicles were proposed. These vehicles have a strong potential to increase the cruise range efficiency at high Mach numbers, thanks to efficient propulsion units combined with high-lifting vehicle concepts. In this framework the Hexafly-INT project has the scope to test in free-flight conditions an innovative gliding vehicle with several breakthrough technologies on-board. This work describes the aero-thermal design processes of the Hexafly-INT Experimental Flight Test Vehicle, namely EFTV. © 2016, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Free flight

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A single-axis pointing magnetic control method for microsatellite

A single-axis pointing magnetic control method for microsate...

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International Conference on Information and Automation (ICIA)

作者： Yimin Kou Chun Li Qin Yuan Yanbo Ji Yingchun Zhang Department of Overall System Design Shenzhen Aerospace Dongfanghong Development Satellite Co. Ltd Shenzhen Province China Control Science and Engineering Department Harbin Institute of Technology Harbin Province China

ISBN: (纸本)9781509041039

To meet the requirements of single-axis pointing in safety modes and other specific tasks of microsatellites, this paper presents a single-axis pointing magnetic control method. This method comprises the following steps: First, use a spatial geometric analysis method to expand the selection range of the rotation axis to an axis plane and then obtain the angular acceleration plane through affine transformation by the inertia matrix. Next, conduct steering control along the intersection of the angular acceleration plane and the axis plane, and meanwhile conduct speed damping control simultaneously in the angular acceleration plane in order to achieve precise single-axis pointing. Compared with traditional methods, the advantages of this method include: undesirable disturbance magnetic torque is hardly generated; it is hardly restricted by the shape and inclination of the orbit; the nondiagonal elements of the inertia matrix are not required to be zero. In the simulation, the method successfully makes a microsatellite point its Z-axis to the ground precisely, which verifies the effectiveness of it.

关键词： Acceleration Magnetomechanical effects Torque Orbits Satellites Angular velocity Magnetic moments

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