检索结果-内蒙古大学图书馆

L-Type Calcium Channel Modulates Low-Intensity Pulsed Ultrasound-Induced Excitation in Cultured Hippocampal Neurons

Neuroscience Bulletin 2024年第7期40卷 921-936页

作者： Wen-Yong Fan Yi-Ming Chen Yi-Fan Wang Yu-Qi Wang Jia-Qi Hu Wen-Xu Tang Yi Feng Qian Cheng Lei Xue State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Fudan UniversityShanghai 200433China Department of Physiology and Neurobiology School of Life SciencesFudan UniversityShanghai 200438China Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education Tongji UniversityShanghai 200070China Center for Rehabilitation Medicine Department of Pain ManagementZhejiang Provincial People's HospitalAffliated People's HospitalHangzhou Medical CollegeHangzhou 310014China Department of Critical Care Medicine Shanghai General HospitalShanghai Jiaotong University School of MedicineShanghai 200080China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China Research Institute of Intelligent Complex Systems Fudan UniversityShanghai 200433China

As a noninvasive technique,ultrasound stimulation is known to modulate neuronal activity both in vitro and in *** latest explanation of this phenomenon is that the acoustic wave can activate the ion channels and further impact the electrophysiological properties of targeted ***,the underlying mechanism of low-intensity pulsed ultrasound(LIPUS)-induced neuro-modulation effects is still ***,we characterize the excitatory effects of LIPUS on spontaneous activity and the intracellular Ca^(2+)homeostasis in cultured hippocampal *** whole-cell patch clamp recording,we found that 15 min of 1-MHz LIPUS boosts the frequency of both spontaneous action potentials and spontaneous excitatory synaptic currents(sEPSCs)and also increases the amplitude of sEPSCs in hippocampal *** phenomenon lasts for>10 min after LIPUS *** with Ca^(2+)imaging,we clarified that LIPUS increases the[Ca^(2+)]cyto level by facilitating L-type Ca^(2+)channels(LTCCs).In addition,due to the[Ca^(2+)]cyto elevation by LIPUS exposure,the Ca^(2+)-dependent CaMKII-CREB pathway can be activated within 30 min to further regulate the gene transcription and protein *** work suggests that LIPUS regulates neuronal activity in a Ca^(2+)-dependent manner via *** may also explain the multi-activation effects of LIPUS beyond *** stimulation potentiates spontaneous neuronal activity by increasing Ca^(2+)influx.

关键词： Low-intensity pulsed ultrasound Neuromodulation L-type calcium channel Hippocampal neuron

来源：评论

学校读者我要写书评

暂无评论

Parallel control-Based Event-Triggered Optimal control for Constrained Discrete-Time Nonlinear systems

Parallel Control-Based Event-Triggered Optimal Control for C...

引用

2021 China Automation Congress, CAC 2021

作者： Lu, Jingwei Bai, Tianxiang Wei, Qinglai Zhou, Tianmin Wang, Fei-Yue School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China

ISBN: (纸本)9781665426473

This study proposes a new event-triggered optimal control (ETOC) method for discrete-time (DT) constrained nonlinear systems. First, a new triggering condition is proposed. We show the asymptotic stability of the closed-loop system using the proposed triggering condition and analyze the degeneration degree of the real performance index. Second, to perform the proposed ETOC method effectively, parallel control (PC) combined with adaptive dynamic programming (ADP) is applied. Finally, the validity of the ETOC method is validated by a simulation. © 2021 IEEE

关键词： Asymptotic stability

来源：评论

学校读者我要写书评

暂无评论

A parallel intelligent system for optimizing high-speed railway rescheduling by learning 1

A parallel intelligent system for optimizing high-speed rail...

引用

1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Yang, Pengxin Cui, Dongliang Dai, Xuewu Lv, Yisheng Dong, Hairong Wang, Xinghao Liu, Ruiguang State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China

ISBN: (纸本)9781665433372

The railway system is a complex system because of many constraints, randomness and high security requirements, so it is difficult to establish an accurate mathematical model for it, which brings great challenges to railway scheduling. Parallel intelligence theory can effectively solve the modeling, analysis and control of complex systems, so it has a wide range of applications in the field of intelligent transportation. In this paper, we build an artificial system according to the actual system, and use the surrogate modelling to carry out the calculation experiments, and proposed a parallel scheduling system based on the parallel intelligence method. Select a case to design scenario and perform computational experiment, the scheduling strategy is given and the scheduling strategy is analyzed. © 2021 IEEE.

关键词： Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

Anomaly detection in digital twin model 1

Anomaly detection in digital twin model

引用

1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Wang, Yutong Cao, Yansong Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Macau Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665433372

As the simulation model of a physical system, digital twin has been widely used in many complicated control systems. Providing an effective way to perform simulation, digital twin makes the evaluation, prediction and optimization process cheaper and easier than on physical systems. For smart manufacturing, digital twin achieves high productivity with less operation and maintenance cost. However, the advantages of digital twin in anomaly detection during manufacturing are always neglected. Taking a two-speed transmission system as an example, we generate three kinds of faults on this digital twin model. After extracting features from the system output, we train an anomaly detection model on these features to classify each type of fault. By this digital twin model, we can find the fault in the whole system at the very beginning, and reduce the time and cost of debugging and diagnosing. © 2021 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

A Novel Heterogeneous Actor-critic Algorithm with Recent Emphasizing Replay Memory

引用

International Journal of Automation and computing 2021年第4期18卷 619-631页

作者： Bao Xi Rui Wang Ying-Hao Cai Tao Lu Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghai 200031China

Reinforcement learning(RL) algorithms have been demonstrated to solve a variety of continuous control tasks. However,the training efficiency and performance of such methods limit further applications. In this paper, we propose an off-policy heterogeneous actor-critic(HAC) algorithm, which contains soft Q-function and ordinary Q-function. The soft Q-function encourages the exploration of a Gaussian policy, and the ordinary Q-function optimizes the mean of the Gaussian policy to improve the training efficiency. Experience replay memory is another vital component of off-policy RL methods. We propose a new sampling technique that emphasizes recently experienced transitions to boost the policy training. Besides, we integrate HAC with hindsight experience replay(HER) to deal with sparse reward tasks, which are common in the robotic manipulation domain. Finally, we evaluate our methods on a series of continuous control benchmark tasks and robotic manipulation tasks. The experimental results show that our method outperforms prior state-of-the-art methods in terms of training efficiency and performance, which validates the effectiveness of our method.

关键词： Reinforcement learning(RL) actor-critic experience replay training efficiency manipulation skill learning

来源：评论

学校读者我要写书评

暂无评论

VistaScenario: Interaction Scenario Engineering for Vehicles with Intelligent systems for Transport Automation

arXiv

引用

arXiv 2024年

作者： Chang, Cheng Zhang, Jiawei Ge, Jingwei Zhang, Zuo Wei, Junqing Li, Li Wang, Fei-Yue DiDi Autonomous Driving Company Beijing100094 China The Department of Automation BNRist Tsinghua University Beijing100084 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and index scenarios, various vehicle interactions are worthy of much attention, and deserve refined descriptions and labels. However, existing methods cannot cope well with the problem of scenario classification and labeling with vehicle interactions as the core. In this paper, we propose VistaScenario framework to conduct interaction scenario engineering for vehicles with intelligent systems for transport automation. Based on the summarized basic types of vehicle interactions, we slice scenario data stream into a series of segments via spatiotemporal scenario evolution tree. We also propose the scenario metric Graph-DTW based on Graph Computation Tree and Dynamic Time Warping to conduct refined scenario comparison and labeling. The extreme interaction scenarios and corner cases can be efficiently filtered and extracted. Moreover, with naturalistic scenario datasets, testing examples on trajectory prediction model demonstrate the effectiveness and advantages of our framework. VistaScenario can provide solid support for the usage and indexing of scenario data, further promote the development of intelligent vehicles and transport automation. Copyright © 2024, The Authors. All rights reserved.

关键词： Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Recurrent Attention and Interaction Model for Pedestrian Trajectory Prediction

引用

IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1361-1370页

作者： Xuesong Li Yating Liu Kunfeng Wang Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the University of Chinese Academy of SciencesBeijing 100049China College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

The movement of pedestrians involves temporal continuity,spatial interactivity,and random *** a result,pedestrian trajectory prediction is rather *** existing trajectory prediction methods tend to focus on just one aspect of these challenges,ignoring the temporal information of the trajectory and making too many *** this paper,we propose a recurrent attention and interaction(RAI)model to predict pedestrian *** RAI model consists of a temporal attention module,spatial pooling module,and randomness modeling *** temporal attention module is proposed to assign different weights to the input sequence of a target,and reduce the speed deviation of different *** spatial pooling module is proposed to model not only the social information of neighbors in historical frames,but also the intention of neighbors in the current *** randomness modeling module is proposed to model the uncertainty and diversity of trajectories by introducing random *** conduct extensive experiments on several public *** results demonstrate that our method outperforms many that are state-ofthe-art.

关键词： Deep learning long short-term memory(LSTM) recurrent attention and interaction(RAI)model trajectory prediction

来源：评论

学校读者我要写书评

暂无评论

Pedestrian Trajectory Prediction by Modeling the Interactions using Social LSTM Extensions

Pedestrian Trajectory Prediction by Modeling the Interaction...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Si, Zeze Zhao, Hongxia Tang, Haina Zhu, Fenghua Lv, Yisheng Lu, Hao Institute of Autamation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Qingdao Academy of Intelligent Industries Qingdao266000 China

ISBN: (纸本)9781665465335

In many driving situations, human mobility is an important topic in trajectory prediction. Considering the pedestrian trajectory as a sequence generative task, a prediction algorithm based on Social Long Short-Term Memory (Social LSTM) is implemented. In order to simulate the social interaction between pedestrians, Social Pooling (S-Pooling) is used to aggregate the hidden state of pedestrians, while the attention mechanism is utilized to aggregate information differently according to the importance of surrounding pedestrians. Furthermore, Convolutional Neural Networks (CNN) is introduced into Social LSTM model to consider both the interaction between people and the characteristic of scene scale in the prediction process. Experiments are carried out against baseline methods, and the results demonstrated that combining Social LSTM with attention mechanism or CNN can improve the performance of pedestrian trajectory prediction. © 2022 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Optimal synchronization control formulti-agent systems with input saturation:a nonzero-sum game

引用

Frontiers of Information Technology & Electronic Engineering 2022年第7期23卷 1010-1019页

作者： Hongyang LI Qinglai WEI School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

This paper presents a novel optimal synchronization control method for multi-agent systems with input *** multi-agent game theory is introduced to transform the optimal synchronization control problem into a multi-agent nonzero-sum ***,the Nash equilibrium can be achieved by solving the coupled Hamilton–Jacobi–Bellman(HJB)equations with nonquadratic input energy terms.A novel off-policy reinforcement learning method is presented to obtain the Nash equilibrium solution without the system models,and the critic neural networks(NNs)and actor NNs are introduced to implement the presented *** analysis is provided,which shows that the iterative control laws converge to the Nash *** results show the good performance of the presented method.

关键词： Optimal synchronization control Multi-agent systems Nonzero-sum game Adaptive dynamic programming Input saturation Off-policy reinforcement learning Policy iteration

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：