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1,034 results on '"Lu, Liming"'

51. Contributors

Author

Ahmed, Hesham, primary, Babich, Alexander, additional, Bensley, S., additional, Boxall, Naomi J., additional, Bruckard, Warren J., additional, Clout, J.M.F., additional, Crisafio, C., additional, Donskoi, E., additional, Dwyer, Rebecca B., additional, Fisher-White, Michael J., additional, Gerrans, T., additional, Han, Hongliang, additional, Haque, Nawshad, additional, Hartmann, M.J., additional, Heyes, Graeme W., additional, Higuchi, Takahide, additional, Higuchi, Kenichi, additional, Holmes, Ralph J., additional, Ishiyama, Osamu, additional, Jankovic, Aleksandar, additional, Lau, Ian, additional, Laukamp, Carsten, additional, Li, Xianchun, additional, Lovel, Roy R., additional, Lu, Yifan, additional, Lu, Liming, additional, Manuel, J.R., additional, Maré, E., additional, Matsumura, Masaru, additional, Mousa, Elsayed, additional, Nomura, Seiji, additional, Ooi, Tze Chean, additional, Oosthuizen, J.P., additional, Pan, Jian, additional, Poliakov, A., additional, Ramanaidou, Erick, additional, Rea, Suzanne M., additional, Senk, Dieter, additional, Smith, Leanne K., additional, Sparrow, Graham J., additional, Stace, R., additional, Tonžetić, Igor Željko, additional, de Villiers, Johan P.R., additional, Wells, Martin, additional, Weng, Zhehan, additional, Werner, Tim T., additional, Xiong, Dahe, additional, Yellishetty, Mohan, additional, and Zhu, Deqing, additional

Published
2022
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69. A Novel Robotic Path Planning Method in Grid Map Context Based on D* Lite Algorithm and Deep Learning.

Author

Lin, Zhen, Lu, Liming, Yuan, Yu, and Zhao, Hong

Subjects
*DEEP learning, *MOBILE robots, *ROBOTIC path planning, *MACHINE learning, *GRIDS (Cartography), *DEEP reinforcement learning, *REINFORCEMENT learning
Abstract

Mobile robot path planning has received more and more attention as an important technology in robotics. Based on the D* Lite algorithm, this paper constructs a robot path planning model in a grid map environment, and proposes a deep learning fusion algorithm for path planning under complex large maps. The D* Lite algorithm with excellent performance adopts the enhanced neural network algorithm with environment self-learning ability for local parts. The model introduces the gentle update method of the Q value in the D* Lite algorithm into the optimization target calculation, calculates the loss function and updates the network parameters, thereby solving the overestimation problem of deep reinforcement learning in the application of mobile robot path planning. In the simulation process, the idea of averaging is introduced into the e-greedy strategy, and the value function output by the previous generation parameter network is used to obtain the average result to determine the next action direction of the mobile robot. The experimental results show that in the simple environment and the complex environment, the planned path lengths in the environment are 44.21, 43.63 and 43.61 m, respectively, reducing the number of collisions with obstacles during the training process of the mobile robot, and improving the superiority and effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Published
2024
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72. Complementary and Alternative Medicine for Substance Use Disorders: A Scientometric Analysis and Visualization of Its Use Between 2001 and 2020

Author

Jiao Junyue, Chen Siyu, Wang Xindong, Xiao Qinge, Zeng Jingchun, Lu Liming, and Lin Guohua

Subjects
acupuncture, bibliometrics [MeSH], complementary therapies, substance-related disorders, science map, Psychiatry, RC435-571
Abstract

Background: This study aimed to identify frontiers for further studies via brief understanding in complementary and alternative medicine (CAM) for substance use disorders (SUDs).Materials and Methods: Publications on the use of CAM for treating SUDs were retrieved from the Web of Science Core Collection from 2001 to 2020 on July 12, 2020, and visualized by CiteSpace V.Results: A total of 3,807 publications were obtained. The USA, China, and England were the leading research centers. However, India and Pakistan have recently focused on assessing CAM for the treatment of SUDs. Frederick L Altice was found to be the most productive author. Addiction ranked first among the frequently cited journals, which exceeded 1,000. The most common CAM therapies were acupuncture and CAM psychotherapies, such as mindfulness meditation.Conclusion: CAM is gaining attention globally for treating SUDs. CAM psychotherapy and acupuncture are hotspots and deserve further study. Researchers should strengthen peer cooperation in this field.

Published
2021
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84. TEMPORARY REMOVAL: Quantitative studies on the microstructure of ternary CaO–Al2O3–SiO2 glasses by Raman spectroscopy, 27Al MAS NMR and quantum chemistry ab initio calculation

Author

Tang, Xiaohui, primary, You, Jinglin, additional, Wang, Jian, additional, Zhang, Fu, additional, Gong, Xiaoye, additional, Xie, Yingfang, additional, Canizarès, Aurélien, additional, Bessada, Catherine, additional, Tang, Kai, additional, and Lu, Liming, additional

Published
2023
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90. Establishment of porcine and human expanded potential stem cells

Author

Gao, Xuefei, Nowak-Imialek, Monika, Chen, Xi, Chen, Dongsheng, Herrmann, Doris, Ruan, Degong, Chen, Andy Chun Hang, Eckersley-Maslin, Melanie A., Ahmad, Shakil, Lee, Yin Lau, Kobayashi, Toshihiro, Ryan, David, Zhong, Jixing, Zhu, Jiacheng, Wu, Jian, Lan, Guocheng, Petkov, Stoyan, Yang, Jian, Antunes, Liliana, Campos, Lia S., Fu, Beiyuan, Wang, Shengpeng, Yong, Yu, Wang, Xiaomin, Xue, Song-Guo, Ge, Liangpeng, Liu, Zuohua, Huang, Yong, Nie, Tao, Li, Peng, Wu, Donghai, Pei, Duanqing, Zhang, Yi, Lu, Liming, Yang, Fengtang, Kimber, Susan J., Reik, Wolf, Zou, Xiangang, Shang, Zhouchun, Lai, Liangxue, Surani, Azim, Tam, Patrick P. L., Ahmed, Asif, Yeung, William Shu Biu, Teichmann, Sarah A., Niemann, Heiner, and Liu, Pentao

Published
2019
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