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IEEE International Conference on Robotics and Automation (ICRA)

作者： Dongjae Lee Sunwoo Hwang Jeonghyun Byun Seung Jae Lee H. Jin Kim Department of Aerospace Engineering Seoul National University (SNU) Seoul South Korea Department of Mechanical System Design Engineering Seoul National University of Science and Technology (SEOULTECH) Seoul South Korea Department of Aerospace Engineering and Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University Seoul Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Aerial unperching of multirotors has received little attention as opposed to perching that has been investigated to elongate operation time. This study presents a new aerial robot capable of both perching and unperching autonomously on/from a ferromagnetic surface during flight, and a switching controller to avoid rotor saturation and mitigate overshoot during transition between free-flight and perching. To enable stable perching and unperching maneuvers on/from a vertical surface, a lightweight (≈ 1 kg), fully actuated tiltrotor that can hover at 90 ◦ pitch angle is first developed. We design a perching/unperching module composed of a single servomotor and a magnet, which is then mounted on the tiltrotor. A switching controller including exclusive control modes for transitions between free-flight and perching is proposed. Lastly, we propose a simple yet effective strategy to ensure robust perching in the presence of measurement and control errors and avoid collisions with the perching site immediately after unperching. We validate the proposed framework in experiments where the tiltrotor successfully performs perching and unperching on/from a vertical surface during flight. We further show effectiveness of the proposed transition mode in the switching controller by ablation studies where large overshoot and even collision with a perching site occur. To the best of the authors’ knowledge, this work presents the first autonomous aerial unperching framework using a fully actuated tiltrotor.

关键词： Measurement uncertainty Rotors Switches Control systems Autonomous aerial vehicles Task analysis Servomotors

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Numerical Study of the Effective Combination of Microbubbles and Ultrasound in HIFU Therapy

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AIP Conference Proceedings 2011年第1期1359卷 437-442页

作者： Kohei Okita Kazuyasu Sugiyama Kenji Ono Shu Takagi Yoichiro Matsumoto aFunctionality Simulation and Information Team VCAD System Research Program RIKEN 2‐1 Hirosawa Wako Saitama 351‐0198 Japan bDepartment of Mechanical Engineering The University of Tokyo 7‐3‐1 Hongo Bunkyo Tokyo 113‐8656 Japan cOrgan and Body Scale Simulation Team Computational Science Research Program RIKEN 2‐1 Hirosawa Wako Saitama 351‐0198 Japan

The effective combination of microbubbles and ultrasound in HIFU therapy has been investigated through a numerical simulation. The equations for conservation of mass, momentum and energy are solved for a microbubble‐infused mixture, and model HIFU therapy in the presence of microbubbles. The bubbles follow Rayleigh‐Plesset equation, and are coupled with the mixture using the Euler‐Lagrange method. The impacts of both the volume fraction due to the microbubbles and the amplitude of the ultrasound on the heat distribution are analyzed by using a two dimensional cylindrical simulation of the propagation of focused ultrasound (1 MHz) through a mixture of bubbles 1.3 μm in diameter. As the initial void fraction increased, the shape of the high temperature region was observed to change from cigar shape, to tadpole shaped, to cone shape. It was numerically confirmed that the temperature dramatically increased by means of inertial cavitation. The results show that the effectiveness of HIFU therapy increases with increased initial void fraction, as well as an input ultrasound amplitude above the threshold required for inertial cavitation.

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A Study on Giant Magnetostrictive Actuator for Interior Sound Control system of the Ultra-Compact Mobility: Fundamental Consideration on Formation of the Giant Magnetostrictive Phases Depending on Heat Treatment Condition

A Study on Giant Magnetostrictive Actuator for Interior Soun...

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International Conference on Electrical Machines and systems (ICEMS)

作者： Taro Kato Ryusei Naganuma Koki Bando Kentaro Sawada Wu Wenbao Ikkei Kobayashi Jumpei Kuroda Daigo Uchino Kazuki Ogawa Keigo Ikeda Ayato Endo Hideaki Kato Takayoshi Narita Mitusaki Furui Department of Mechanical Engineering Tokyo University of Technology Hachioji-shi Tokyo Japan Sustainable Engineering Program Graduate School of Engineering Tokyo University of Technology Hachioji-shi Tokyo Japan Course of Mechanical Engineering Tokai University Hiratsuka-shi Kanagawa Japan Course of Science and Technology Tokai University Hiratsuka-shi Kanagawa Japan Department of Mechanical Engineering National Institute of Technology (KOSEN) Numazu College Numazu-shi Shizuoka Japan Department of Electronic Robotics Aichi University of Technology Gamagori-shi Aichi Japan Department of Mechanical Engineering Hokkaido University of Science Sapporo Hokkaido Japan Department of Electrical Engineering Fukuoka Institute of Technology Fukuoka-shi Fukuoka Japan Department of Mechanical System Engineering Tokai University Hiratsuka-shi Kanagawa Japan

ISBN: (数字)9784886864406

ISBN: (纸本)9798350379105

An active noise control system using giant magnetostrictive actuator has been proposed as a countermeasure for interior noise of the ultra-compact mobilities, which is a new transportation tools. In this paper, as basic research toward the development of the proposed giant magnetostrictive actuator for active noise control, we conduct experiments on the material properties when terbium, dysprosium, and iron powder, which make up the giant magnetostrictive material, are mixed and the heat treatment conditions are changed. In this study, the heat treatment temperature was varied from $800^{\circ}\mathrm{C}$ to $1100^{\circ}\mathrm{C}$ in $100^{\circ}\mathrm{C}$ incrementsbased on the equilibrium state temperature of each material, and the heat treatment time was set in 30-minute increments from 1 hour to 3 hours. As a result, TbFe2 was confirmed after heat treatment at an electric furnace temperature of $1000^{\circ}\mathrm{C}$ for 3 hours, although its strength was insufficient.

关键词： Actuators Heat treatment Powders Temperature Magnetostriction Noise Terbium Iron Resistance heating Material properties

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A Study on Giant Magnetostrictive Actuator for Interior Soun...

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27th International Conference on Electrical Machines and systems, ICEMS 2024

作者： Kato, Taro Naganuma, Ryusei Bando, Koki Sawada, Kentaro Wenbao, Wu Kobayashi, Ikkei Kuroda, Jumpei Uchino, Daigo Ogawa, Kazuki Ikeda, Keigo Endo, Ayato Kato, Hideaki Narita, Takayoshi Furui, Mitusaki Tokyo University of Technology Department of Mechanical Engineering 1404-1 Katakura Hachioji-shi Tokyo192-0982 Japan Sustainable Engineering Program Graduate School of Engineering Tokyo University of Technology 1404-1 Katakura Hachioji-shi Tokyo192-0982 Japan Tokai University Kitakaname 4-1-1 Kanagawa Hiratsuka-shi259-1292 Japan Tokai University Kitakaname 4-1-1 Kanagawa Hiratsuka-shi259-1292 Japan Numazu College Department of Mechanical Engineering Ohoka 3600 Shizuoka Numazu-shi410-0022 Japan Aichi University of Technology Department of Electronic Robotics 50-2 Manori Nishisako-machi Aichi Gamagori-shi443-0047 Japan Hokkaido University of Science Department of Mechanical Engineering 7-Jo 15-4-1 Maeda Teine Hokkaido Sapporo006-8585 Japan Fukuoka Institute of Technology Department of Electrical Engineering Wajiro Higashi 3-30-1 Higashi-ku Fukuoka Fukuoka-shi811-0295 Japan Tokai University Department of Mechanical System Engineering Kitakaname 4-1-1 Kanagawa Hiratsuka-shi259-1292 Japan

ISBN: (纸本)9784886864406

An active noise control system using giant magnetostrictive actuator has been proposed as a countermeasure for interior noise of the ultra-compact mobilities, which is a new transportation tools. In this paper, as basic research toward the development of the proposed giant magnetostrictive actuator for active noise control, we conduct experiments on the material properties when terbium, dysprosium, and iron powder, which make up the giant magnetostrictive material, are mixed and the heat treatment conditions are changed. In this study, the heat treatment temperature was varied from 800°C to 1100°C in 100°C incrementsbased on the equilibrium state temperature of each material, and the heat treatment time was set in 30-minute increments from 1 hour to 3 hours. As a result, TbFe2 was confirmed after heat treatment at an electric furnace temperature of 1000°C for 3 hours, although its strength was insufficient. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Active noise control

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Super-Fast and Accurate Nonlinear Foot Deformation Prediction Using Graph Neural Networks

SSRN

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SSRN 2024年

作者： Kang, Taehyeon Kim, Jiho Lee, Hyobi Yum, Haeun Kwon, Chani Lee, Sangryun Lee, Taeyong Department of Mechanical and Biomedical Engineering Ewha Womans University Seoul03760 Korea Republic of Department of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Human Performance Lab Co. Ltd. #123a 150 Bugahyeon-ro Seodaemun-gu Seoul03759 Korea Republic of Ewha Womans University Korea Republic of

Recently, there has been a significant increase in the number of foot diseases, highlighting the importance of non-surgical treatments. Customized insoles, tailored to an individual's foot morphology, have emerged as a promising solution. However, the traditional design process of the customized insole is both slow and expensive due to the high computational complexity of finite element analysis (FEA) required to predict deformations of the foot. This study explores the applicability of a graph neural network (GNN) based on the MeshGraphNet framework to predict the 3-D shape of the foot under load and test the performance of GNN depending on the number of datasets. A total of 186 3-D undeformed foot CAD geometries are obtained from a series of 2-D foot images with deformations predicted through FEA. This FEA data is then used to train the GNN model, which aims to predict foot displacement with high accuracy and computation speed. After optimization of the weights of the GNN, the model remarkably outperformed FEA simulations in speed, being approximately 100 times faster, while maintaining high accuracy, with R2 values above 95% in predicting foot displacement. This breakthrough suggests that GNN models can greatly improve the efficiency and reduce the cost of manufacturing customized insoles, providing a significant advancement in non-surgical treatment options for foot conditions. © 2024, The Authors. All rights reserved.

关键词： Forecasting

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mechanical therapeutic effects in osteoporotic L1-vertebrae evaluated by nonlinear patient-specific finite element analysis

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Journal of Biomechanical science and engineering 2010年第5期5卷 499-514页

作者： Tawara, Daisuke Sakamoto, Jiro Murakami, Hideki Kawahara, Norio Oda, Juhachi Tomita, Katsuro Department of Mechanical and Systems Engineering Ryukoku University 1-5 Yokotani Seta Otsu Shiga 520-2194 Japan Computational Cell Biomechanics Team VCAD System Research Program RIKEN 2-1 Hirosawa Wako Saitama 351-0198 Japan School of Mechanical Engineering College of Science and Engineering Kanazawa University Kakuma-machi Kanazawa 920-1192 Japan Department of Orthopedic Surgery Kanazawa University Hospital 13-1 Takara-machi Kanazawa 920-8641 Japan

Patient-specific nonlinear finite element analysis (FEA) is promising for evaluating the recovery of vertebral strength. Vertebral strength is closely related to inner vertebral stress distribution and is used to assess the fracture risk for individual osteoporotic patients during drug treatment. Moreover, stress distribution is affected by individual bone shape, bone density distribution and nonlinear behavior of the mechanical properties of bone. To investigate the effectiveness of FEA considering these factors for the evaluation of drug treatment effects, patient-specific nonlinear FEAs of the first lumbar vertebrae in patients undergoing a 3-year drug treatment were performed. Changes in fracture load and distribution of failure elements in the FE models at four time points (before therapy, and after 6 and 12 months and 3 years of therapy) were compared with those of average bone density. The FEAs demonstrated that failure elements decreased notably, and fracture load increased gradually by the 3-year time point, suggesting that the vertebrae were strengthened as a result of drug treatments. Furthermore, statistical tests indicated that mechanical evaluation using the nonlinear FEAs is more sensitive for evaluating drug effects on osteoporotic bone than assessments based on average bone density. © 2010 by JSME.

关键词： Bone

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EMERGENCY ASCENT . A DEEP SUBMERSIBLES LAST HOPE FOR RETURN

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NAVAL ENGINEERS JOURNAL 1969年第6期81卷 23-&页

作者： JONES, RA Mr. Robert A. Jones is a Naval Architect in the Deck Systems Branch of the Naval Ship Engineering Center Hyattsville Md. He holds a Bachelor of Science degree in Mechanical Engineering from the University of Illinois. Upon joining NAVSEC in 1965 he completed the Hull Systems and Weapons Support Division Junior Engineer Training Program and was then assigned to his present position which includes design and system engineering for submersible vehicle mechanical system equipment jettisoning system underwater work tools and submersible vehicle certification. He is a Registered Engineer in Training in the State of Illinois. He is a member of the Marine Technology Society and the Association of Senior Engineers of the Naval Ship Systems Command.

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Movement Persuit Control of an Offshore Automated Platform via a RAM-based Neural Network

Movement Persuit Control of an Offshore Automated Platform v...

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International Conference on Control, Automation, Robotics and Vision

作者： Horacio L. Franca Joao Carlos P. da Silva Omar Lengerke Max S. Dutra Massimo De Gregorio Felipe M. G. Franca Computer Science Department Mathematics Institute Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Mechanical Engineering Program COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Istituto di Cibernetica "Eduardo Caianiello" Consiglio Nazionale delle Ricerche (CNR) Naples Italy System Engineering and Computer Science Program COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781424478149

The reproduction of the movements of a ship by automated platforms, without the use of sensors providing exact data related to the numeric variables involved, is a non-trivial matter. The creation of an artificial vision system that can follow the cadence of said ship, in six axes of freedom, is the goal of this research. Considering that a real time response is a requisite in this case, it was decided to adopt a Boolean artificial neural network system that could identify and follow arbitrary interest points that could define, as a group, a model of the movement of an observed vessel. This paper describes the development of a prototype based on the Boolean perceptron model WiSARD (Wilkie, Stonham and Aleksander's Recognition Device), that is being implemented in the C programming language on a desktop computer using a regular webcam as input.

关键词： Stewart platform weightless neural networks WiSARD

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Mapping Radionuclide Concentrations in the Uae Using a Gaussian Process Machine Learning Approach

SSRN

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SSRN 2024年

作者： Khuwaileh, Bassam A. Almomani, Belal El-Sayed, Samar Ajaj, Rahaf Akram, Yumna Nuclear Engineering Program Department of Mechanical and Nuclear Engineering University of Sharjah Sharjah27272 United Arab Emirates Nuclear Energy System Simulation and Safety Research Group Sustainable Energy & Power Systems Research Centre RISE University of Sharjah 27272 United Arab Emirates College of Health Science Abu Dhabi University Abu Dhabi United Arab Emirates

This study introduces a machine learning approach for mapping soil radionuclide concentrations in the UAE using Gaussian Process (GP) regression. Aimed at enhancing environmental monitoring and public health, the approach utilizes soil samples from across the UAE to create a radiation map (covering Ra-226, Th-232, and K-40 isotopes). GP regression, known for its proficiency in spatial data interpolation, predicts radionuclide levels in areas without direct testing. This method is adept at managing the non-linear spatial complexities inherent in geographic data, offering both a qualitative and quantitative understanding beneficial for decision-making and further sampling strategies. The results reveal the GP model's capacity to accurately reflect geographic variances in isotopic concentrations, with RMSE values of 13%, 14%, and 22% for Ra-226, Th-232, and K-40, respectively. The model's success in learning the geographical variations of the concentrations showcases its potential to guide future research by identifying areas of increased radioactivity risk. © 2024, The Authors. All rights reserved.

关键词： Machine learning

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