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Reviewing continual learning from the perspective of human-level intelligence

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arXiv 2021年

作者： Chang, Yifan Li, Wenbo Peng, Jian Tang, Bo Kang, Yu Lei, Yinjie Gui, Yuanmiao Zhu, Qing Liu, Yu Li, Haifeng The State Key Laboratory of Fire Science Department of Automation and Institute of Advanced Technology University of Science and Technology of China Hefei China Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China The Department of Electrical and Computer Engineering Mississippi State University United States College of Electronics and Information Engineering Sichuan University Chengdu China Faculty of Geosciences and Environmental Engineering The Southwest Jiaotong University Chengdu China Institute of Remote Sensing and Geographic Information System Peking Universit Beijing China School of Geosciences and Info-Physics Central South University South Lushan Road Changsha410083 China

Humans continual learning (CL) ability is closely related to Stability Versus Plasticity Dilemma that describes how humans achieve ongoing learning capacity and preservation for learned information. The notion of CL has always been present in artificial intelligence (AI) since its births. This paper proposes a comprehensive review of CL. Different from previous reviews that mainly focus on the catastrophic forgetting phenomenon in CL, this paper surveys CL from a more macroscopic perspective based on the Stability Versus Plasticity mechanism. Analogous to biological counterpart, "smart" AI agents are supposed to i) remember previously learned information (information retrospection);ii) infer on new information continuously (information prospection:);iii) transfer useful information (information transfer), to achieve high-level CL. According to the taxonomy, evaluation metrics, algorithms, applications as well as some open issues are then introduced. Our main contributions concern i) rechecking CL from the level of artificial general intelligence;ii) providing a detailed and extensive overview on CL topics;iii) presenting some novel ideas on the potential development of CL. © 2021, CC BY.

关键词： Petroleum reservoir evaluation

A Comprehensive Study on Li4si1-xtixo4 Ceramics for Advanced Tritium Breeders

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Research Square

Research Square 2020年

作者： Gong, Yichao Liu, Lin Qi, Jianqi Yang, Mao Li, Junjie Wang, Hailiang Guo, Hao Zhang, Guojun Lu, Tiecheng School of Materials Science & Engineering Xi’an University of Technology Xi’an710048 China College of Physical Science and Technology Sichuan University Chengdu610064 China Institute of Nuclear Physics and Chemistry China Academy of Engineering Physics Mianyang621900 China

Hetero-elements doped lithium orthosilicate has been considered as advanced tritium breeders due to its superior performances. In this work, Li4Si1-xTixO4 ceramics were prepared by proprietary hydrothermal process and multistage sintering. The reaction mechanism of Li4Si1-xTixO4 was put forward. XRD and SEM analyses indicate that insertion of Ti leads to lattice expansion, enhances the sinterability and changes the fracture mode. The compressive tests show that the crush load increases almost four times by increasing x from 0 to 0.2. However, the thermal conductivity and ionic conductivity are the best when x=0.05 and x=0.1, respectively. Thermal cycling stability of Li4Si1-xTixO4 pebbles was further appraised through investigating the changes of microstructure and crush load. After undergoing thermal cycling, the Li4Si1-xTixO4 still show higher crush load compared with Li4SiO4, despite Ti segregation in some samples. The x=0.05 sample exhibits excellent thermal cycling stability. To be sure, Ti doping improves the overall performance of Li4SiO4 © 2020, CC BY.

关键词： Ionic conductivity

Production of the T+ccstate in the γp → D+T¯-ccΛ+creaction

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arXiv 2021年

作者： Huang, Yin Zhu, Hong Qiang Geng, Li-Sheng Wang, Rong School of Physical Science and Technology Southwest Jiaotong University Chengdu610031 China College of Physics and Electronic Engineering Chongqing Normal University Chongqing401331 China School of Physics and Nuclear Energy Engineering Beihang University Beijing100191 China Institute of Modern Physics Chinese Academy of Sciences Lanzhou730000 China University of Chinese Academy of Sciences Beijing100049 China

Stimulated by the recent LHCb observation of a new exotic charged structure T+cc, we propose to use the central diffractive mechanism existing in the γp→D+T¯-ccΛ+c(T¯ccis antiparticle of T+cc) reaction to produce T+cc. Our theoretical approach is based on the chiral unitary theory where the T+cc} resonance is dynamically generated. With the coupling constant of the T+ccto DD∗channel obtained from chiral unitary theory, the total cross sections of the γp→D+T¯-ccΛ+creaction are evaluated. Our study indicates that the cross section for γp→D+T¯-ccΛ+creaction are of the order of 1.0 pb, which is accessible at the proposed EicC [27] and US-EIC [28] due to the higher luminosity. If measured in future experiments, the predicted total cross sections can be used to test the (molecular) nature of the T+cc © 2021, CC BY.

关键词：

Simulation Study on Scaler Mode in LHAASO-KM2A 37

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Simulation Study on Scaler Mode in LHAASO-KM2A

37th International Cosmic Ray Conference, ICRC 2021

作者： Huang, Zhicheng Huang, Daihui Zhou, Xunxiu Zhao, Jing He, Huihai Chen, Songzhan Ma, Xinhua Liu, Dong Axi, Kegu Zhao, Bing Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, L.X. Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, H. Cai, J.T. Cao, Zhe Chang, J. Chang, J.F. Chen, B.M. Chen, E.S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, X.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, S.W. Cui, X.H. Cui, Y.D. D’Ettorre Piazzoli, B. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.J. Duan, K.K. Fan, J.H. Fan, Y.Z. Fan, Z.X. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, Y.L. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Ge, M.M. Geng, L.S. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, J.G. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.C. He, S.L. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, C. Hu, H.B. Hu, S. Hu, S.C. Hu, X.J. Huang, D.H. Huang, Q.L. Huang, W.H. Huang, X.T. Huang, X.Y. Huang, Z.C. Ji, F. Ji, X.L. Jia, H.Y. Jiang, K. Jiang, Z.J. Jin, C. Ke, T. Kuleshov, D. Levochkin, K. Li, B.B. Li, Cheng Li, Cong Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, K. Li, W.L. Li, X.R. Li, Xin Li, Xin Li, Y. Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.S. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Liu, Z.X. Long, W.J. Lu, R. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Masood, A. Min, Z. Mitthumsiri, W. Montaruli, T. Nan, Y.C. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Rulev, V. Saiz, A. Shao, L. Shchegolev, O. Sheng, X.D. Shi, J.Y. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. School of Physical Science and Technology Southwest Jiaotong University Chengdu610031 China Institute of High Energy Physics CAS Beijing100049 China Institute of Frontier and Interdisciplinary Science Shandong University Qingdao266237 China Key Laboratory of Particle Astrophyics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China College of Physics Sichuan University Sichuan Chengdu610065 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China School of Physics and Technology Wuhan University Hubei Wuhan430072 China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-Sen University Guangdong Zhuhai519000 China Dipartimento di Fisica Universit‘a di Napoli "Federico II" Complesso Universitario di Monte Sant’Angelo via Cinthia Napoli80126 Italy School of Physics and Astronomy Yunnan U

LHAASO, located at Daocheng in Sichuan province of China with an altitude up to 4410 m above the sea level, takes the function of hybrid technology to detect cosmic rays. As the major array of LHAASO, KM2A is composed of 5195 electromagnetic particle detectors (EDs) and 1188 muon detectors (MDs). In the ground-based experiments, there are two common independent data acquisition systems, corresponding to the scaler and shower operation modes. In order to learn more about the scaler mode in LHAASO-KM2A, we adopt the CORSIKA to study the shower development and employ the G4KM2A (based on Geant4) to simulate the detector responses. For one cluster (composed of 64 EDs) in the array of KM2A-ED, the event rates of showers having a number of fired EDs ≥ 1, 2, 3 and 4 (in a time coincidence of 100 ns) are recorded. The average rates of the four multiplicities are ∼ 88 kHz, ∼ 1.4 kHz, ∼ 210 Hz and ∼ 110 Hz, respectively. For the array of KM2A-MD, there are 16 MDs in one cluster. The average rates with multiplicities ≥ 1 and 2 are ∼ 84 kHz and ∼ 890 Hz, respectively. The corresponding primary energies are also given. According to our simulations, the energy threshold of the scaler mode can be lowered to ∼ 100 GeV. At the same time, the energy threshold of LHAASO-KM2A in shower mode is presented for comparison. The simulation results in this work are beneficial for the online trigger with scaler mode, and also be useful in understanding the experiment results in LHAASO-KM2A. © Copyright owned by the author(s).

关键词： Cosmic rays

ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data

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arXiv 2023年

作者： Zhong, Tianyang Zhao, Wei Zhang, Yutong Pan, Yi Dong, Peixin Jiang, Zuowei Kui, Xiaoyan Shang, Youlan Yang, Li Wei, Yaonai Yang, Longtao Chen, Hao Zhao, Huan Liu, Yuxiao Zhu, Ning Li, Yiwei Wang, Yisong Yao, Jiaqi Wang, Jiaqi Zeng, Ying He, Lei Zheng, Chao Zhang, Zhixue Li, Ming Liu, Zhengliang Dai, Haixing Wu, Zihao Zhang, Lu Zhang, Shu Cai, Xiaoyan Hu, Xintao Zhao, Shijie Jiang, Xi Zhang, Xin Li, Xiang Zhu, Dajiang Guo, Lei Shen, Dinggang Han, Junwei Liu, Tianming Liu, Jun Zhang, Tuo School of Automation Northwestern Polytechnical University Xi’an710072 China The Second Xiangya Hospital Central South University Changsha410011 China Clinical Research Center for Medical Imaging in Hunan Province Changsha China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Institute of Medical Research Northwestern Polytechnical University Xi’an710072 China Glasgow College University of Electronic Science and Technology of China Chengdu611731 China School of Life Science and Technology University of Electronic Science and Technology of China Chengdu611731 China School of Computer Science and Engineering Central South University Hunan Province Changsha410083 China School of Biomedical Engineering ShanghaiTech University Shanghai201210 China Lingang Laboratory Shanghai200031 China Imaging Center The Second Affiliated Hospital of Xinjiang Medical University Urumuqi830000 China School of Computer Science Northwestern Polytechnical University Xi’an710072 China Department of Radiology Xiangtan Central Hospital Xiangtan411199 China Department of Radiology Yueyang Central Hospital City Yueyang414000 China Department of Radiology The First People's Hospital of Changde City Changde415003 China Department of Radiology The First Hospital of Hunan University of Chinese Medicine Changsha410021 China Department of Radiology Huadong Hospital Affiliated to Fudan University Shanghai200040 China School of Computing University of Georgia GA United States Department of Computer Science and Engineering University of Texas ArlingtonTX United States Department of Radiology Massachusetts General Hospital Harvard Medical School MA United States Shanghai United Imaging Intelligence Co. Ltd. China Shanghai Clinical Research and Trial Center China

Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and diverse radiology reports with cross-source heterogeneity pose a huge generalizability challenge to the current methods under massive data volume, mainly because the style and normativity of radiology reports are obviously distinctive among institutions, body regions inspected and radiologists. Recently, the advent of large language models (LLM) offers great potential for recognizing signs of health conditions. To resolve the above problem, we collaborate with the Second Xiangya Hospital in China and propose ChatRadio-Valuer based on the LLM, a tailored model for automatic radiology report generation that learns generalizable representations and provides a basis pattern for model adaptation in sophisticated analysts' cases. Specifically, ChatRadio-Valuer is trained based on the radiology reports from a single institution by means of supervised fine-tuning, and then adapted to disease diagnosis tasks for human multi-system evaluation (i.e., chest, abdomen, muscle-skeleton, head, and maxillofacial & neck) from six different institutions in clinical-level events. The clinical dataset utilized in this study encompasses a remarkable total of 332,673 observations. From the comprehensive results on engineering indicators, clinical efficacy and deployment cost metrics, it can be shown that ChatRadio-Valuer consistently outperforms state-of-the-art models, especially ChatGPT (GPT-3.5-Turbo) and GPT-4 et al., in terms of the diseases diagnosis from radiology reports. ChatRadio-Valuer provides an effective avenue to boost model generalization performance and alleviate the annotation workload of experts to enable the promotion of clinical AI applications in radiology reports. © 2023, CC BY.

关键词： Decision making

An LQG Optimal Linear Controller for Fin Stabilizer System of Marine Vessels

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An LQG Optimal Linear Controller for Fin Stabilizer System o...

International Conference on System Science and engineering (ICSSE)

作者： QuangDuy Nguyen Tieshan Li Renhai Yu Qihe Shan Yue Wu Jun Ning Navigation College Dalian Maritime University Dalian China Faculty of Navigation Vietnam Maritime University Haiphong Vietnam School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728159607

ISBN: (纸本)9781728159614

When sailing at sea, the ship's rolling motion will greatly affect the safety of the ship and the cargo, as well as the health of the crew. As a common means for roll reduction, active fins are usually installed on ships, and the roll reduction efficiency of these fins depends primarily on the controller. In our work, a Linear Quadratic Gaussian (LQG) optimal controller is proposed for the ship linear fin stabilizer system. Specifically, this LQG control method is combined by the linear quadratic regulator (LQR) method and the linear quadratic estimator (LQE) method, the latter of which is also known as the Kalman filter. Therefore, the separation principle is used in this paper to solve the roll reduction problem of ships, namely the LQG controller is derived by solving the predestined optimal control problem and the optimal state estimation problem. Finally, the stability and efficiency of the proposed LQG controller is validated by conducting contrast simulation with the LQR controller, and the result of which shows better performance of the designed LQG strategy.

关键词：

Opinion Dynamics Driven Under Leadership in Cooperation-Competition Social Networks

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Opinion Dynamics Driven Under Leadership in Cooperation-Comp...

International Conference on Control and automation (ICCA)

作者： Libing Bai Lei Shi Hongjian Chen Jinliang Shao Yuhua Cheng School of Automation Engineering University of Electronic Science and Technology of China P. R. China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Shen zhen Institute of Artifcial Intelligence and Robotics for Society Shenzhen China Glasgow college University of Electronic Science and Technology of China P. R. China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

Social psychological research shows that although the opinions of most agents (followers) tend to prevail, sometimes a firm and influential agent (leader) can influence or even overturn the followers' preferences. Inspired by this fact, this paper designs a Degreet-model-based opinion evolution rule in cooperation-competition social networks, and uses the relevant properties of the super-stochastic matrix to conduct theoretical analysis on how the leader influence the formation of followers' opinions. Finally, algebraic conditions for achieving leader-driven opinion consensus and opinion polarization are established, respectively. Moreover, the correctness of the theoretical results is verified by numerical simulations.

关键词： Social networking (online) Leadership Psychology automation Systematics Sensitivity Robot sensing systems

Online optimal control for nonlinear fin stabilizer system of marine vessels via time-based ADP algorithm

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Online optimal control for nonlinear fin stabilizer system o...

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： QuangDuy Nguyen Tieshan Li Jun Ning Yue Wu Navigation College Dalian Maritime University Dalian China Faculty of Navigation Vietnam Maritime University Haiphong Vietnam School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

An online optimal control for fin stabilizer system of vessels based on adaptive dynamic programming (ADP) with an unknown system dynamic is developed in this paper. A model network is firstly used to identify the unknown fin stabilizer system dynamic and the optimal control can be obtained by using recorded and current data without knowledge of system dynamic. Then, two neural networks (NN) which are action and critic network are used to approximate the optimal control policy and optimal cost function respectively, two NNs are trained by using current and recorded data of the system and update processing is given for them once at sampling time. The proposed optimal control law can reduce roll motion of vessels at desired value and guarantee all states of the system, control signals and cost function are uniformly ultimately bounded (UUB) with desired bounded errors. Simulation results are given to validate the effectiveness and performance of the proposed optimal control policy.

关键词： System dynamics Simulation Optimal control Process control Artificial neural networks Cost function Data models

Constraints on the axial-vector and pseudo-scalar mediated WIMP-nucleus interactions from PandaX-4T experiment

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arXiv 2022年

作者： Huang, Zhou Han, Chencheng Abdukerim, Abdusalam Bo, Zihao Chen, Wei Chen, Xun Chen, Yunhua Cheng, Chen Cheng, Zhaokan Cui, Xiangyi Fan, Yingjie Fang, Deqing Fu, Changbo Fu, Mengting Geng, Lisheng Giboni, Karl Gu, Linhui Guo, Xuyuan Han, Ke He, Changda He, Jinrong Huang, Di Huang, Yanlin Hou, Ruquan Ji, Xiangdong Ju, Yonglin Li, Chenxiang Li, Jiafu Li, Mingchuan Li, Shu Li, Shuaijie Lin, Qing Liu, Jianglai Lu, Xiaoying Luo, Lingyin Luo, Yunyang Ma, Wenbo Ma, Yugang Mao, Yajun Meng, Yue Ning, Xuyang Qi, Ningchun Qian, Zhicheng Ren, Xiangxiang Shaheed, Nasir Shang, Changsong Shang, Xiaofeng Shen, Guofang Si, Lin Sun, Wenliang Tan, Andi Tao, Yi Wang, Anqing Wang, Meng Wang, Qiuhong Wang, Shaobo Wang, Siguang Wang, Wei Wang, Xiuli Wang, Zhou Wei, Yuehuan Wu, Mengmeng Wu, Weihao Xia, Jingkai Xiao, Mengjiao Xiao, Xiang Xie, Pengwei Yan, Binbin Yan, Xiyu Yang, Jijun Yang, Yong Yu, Chunxu Yuan, Jumin Yuan, Zhe Zeng, Xinning Zhang, Dan Zhang, Minzhen Zhang, Peng Zhang, Shibo Zhang, Shu Zhang, Tao Zhang, Yingxin Zhang, Yuanyuan Zhao, Li Zheng, Qibin Zhou, Jifang Zhou, Ning Zhou, Xiaopeng Zhou, Yong Zhou, Yubo Shanghai Key Laboratory for Particle Physics and Cosmology Shanghai200240 China School of Physics Beihang University Beijing102206 China Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang University Beijing102206 China School of Physics and Microelectronics Zhengzhou University Henan Zhengzhou450001 China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei230026 China Department of Modern Physics University of Science and Technology of China Hefei230026 China School of Physics Peking University Beijing100871 China Yalong River Hydropower Development Company Ltd. 288 Shuanglin Road Chengdu610051 China Research Center for Particle Science and Technology Institute of Frontier and Interdisciplinary Scienc Shandong University Shandong Qingdao266237 China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Shandong Qingdao266237 China Department of Physics University of Maryland College ParkMD20742 United States Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Physics Sun Yat-Sen University Guangzhou510275 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-Sen University Zhuhai519082 China School of Physics Nankai University Tianjin300071 China Institute of Modern Physics Fudan University Shanghai200433 China School of Medical Instrument and Food Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Jiao Tong University Sichuan Research Institute Chengdu610213 China

We present the constraints on the axial-vector and pseudo-scalar mediated WIMP-nucleus interactions from the PandaX-4T experiment, using the data set corresponding to a total exposure of 0.63 tonne·year. No significant signal excess is observed, and the most stringent constraints to date on the mediator mass are set for the axial-vector and pseudo-scalar simplified models. The maximum excluded mass of an axial-vector mediator is 825 GeV/c2 and that of a pseudo-scalar mediator is 106 GeV/c2. In addition, the upper limits on the spin-dependent WIMP-nucleon scattering cross-section for conventional neutron-only and proton-only interactions are derived. Copyright © 2022, The Authors. All rights reserved.

关键词： Vectors