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Franklin Open 2023年 3卷

作者： Liu, Xingyue Shi, Kaibo Zhou, Kun Wen, Shiping Tang, Yiqian Tang, Lin School of Electronic Information and Electrical Engineering Chengdu University Chengdu 610106 China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang University Hangzhou 310018 China Australian AI Institute Faculty of Engineering and Information Technology University of Technology Sydney Sydney 2007 NSW Australia Engineering Research Center of Power Quality of Ministry of Education Anhui University Hefei 230601 China Institute of Electronic and Information Engineering of University of Electronic Science and Technology of China in Guangdong 523808 China

In this work, the event-triggering-based resilient H∞ load frequency control (LFC) scheme under denial-of-service (DoS) attacks is developed for multi-area cyber–physical power system (MA-CPPS) with electric vehicle... 详细信息

In this work, the event-triggering-based resilient H_∞ load frequency control (LFC) scheme under denial-of-service (DoS) attacks is developed for multi-area cyber–physical power system (MA-CPPS) with electric vehicles (EVs). In MA-CPPS, the sampled measurements are transmitted through the communication network, which may be subjected to the energy-limited DoS attack with a resilient index of maximum allowable continuous data losses. Meanwhile, a novel adaptive event-triggering mechanism (AETM) characterized by parameters disturbances and dynamic adjustment mechanism of triggering threshold can effectively reduce the occupation of network bandwidth and computational burden in practical operation of sampled-data LFC in MA-CPPS. Hence a sampled-data LFC model of considering energy-limited DoS attack and AETM is established firstly. Then based on a novel AETM transmission interval-dependent loop functional approach, a resilient H_∞ state-feedback controller is designed with guaranteed H_∞ performance and resilient index of energy-limited DoS attack. Finally, the effectiveness and superiority of our proposed scheme are verified by one-area and three-areas LFC CPPS. © 2023 The Authors

关键词： Adaptive event-triggering mechanism Cyber–physical power system Denial-of-service attacks Resilient H∞ load frequency control scheme Transmission interval-dependent loop functional approach

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Dynamic Gesture Recognition Algorithm Based on 3D Convolutional Neural Network

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Computational Intelligence and Neuroscience 2021年 2021卷 4828102页

作者： Liu, Yuting Jiang, Du Duan, Haojie Sun, Ying Li, Gongfa Tao, Bo Yun, Juntong Liu, Ying Chen, Baojia Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance China Three Gorges University Yichang443002 China

Gesture recognition is one of the important ways of human-computer interaction, which is mainly detected by visual technology. The temporal and spatial features are extracted by convolution of the video containing gesture. However, compared with the convolution calculation of a single image, multiframe image of dynamic gestures has more computation, more complex feature extraction, and more network parameters, which affects the recognition efficiency and real-time performance of the model. To solve above problems, a dynamic gesture recognition model based on CBAM-C3D is proposed. key frame extraction technology, multimodal joint training, and network optimization with BN layer are used for making the network performance better. The experiments show that the recognition accuracy of the proposed 3D convolutional neural network combined with attention mechanism reaches 72.4% on EgoGesture dataset, which is improved greatly compared with the current main dynamic gesture recognition methods, and the effectiveness of the proposed algorithm is verified. © 2021 Yuting Liu et al.

关键词： Convolution

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Inter-Participant Transfer Learning with Attention Based Domain Adversarial Training for P300 Detection

SSRN

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SSRN 2024年

作者： Li, Shurui Daly, Ian Guan, Cuntai Cichocki, Andrzej Jin, Jing Center of Intelligent Computing School of Mathematics East China University of Science and Technology Shanghai200237 China Brain-Computer Interfacing Neural Engineering Laboratory School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom School of Computer Science and Engineering Nanyang Technological University 639798 Singapore RIKEN Brain Science Institute Wako351–0198 Japan Torun87-100 Poland Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

A Brain-computer interface (BCI) system establishes a novel communication channel between the human brain and a computer. Most event related potential-based BCI applications make use of decoding models, which require training. This training process is often time-consuming and inconvenient for new users. In recent years, deep learning models, especially participant-independent models, have garnered significant attention in the domain of ERP classification. However, individual differences in EEG signals hamper model generalization, as the ERP component and other aspects of the EEG signal vary across participants, even when they are exposed to the same stimuli. This paper proposes a novel One-source Domain transfer based Attention Domain Adversarial Neural Network (OADANN) to mitigate data distribution discrepancies for participant-independent ERP classification tasks. We train and validate our proposed model using both a publicly available OpenBMI dataset and a self-collected dataset, employing a leave-one-participant-out cross-validation scheme. Our experimental results demonstrate that our OADANN method achieves the highest and most robust classification performance and exhibits significant improvements when compared to baseline methods (CNN, EEGNet, ShallowCovNet, DeepCovNet) and domain generalization methods (ERM, Mixup, and Groupdro). These findings underscore the efficacy of our proposed method. © 2024, The Authors. All rights reserved.

关键词： Brain computer interface

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Improving Referring Expression Comprehension by Suppressing Expression-unrelated Proposals

Improving Referring Expression Comprehension by Suppressing ...

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electronic Information Engineering and Computer technology (EIECT), International Conference on

作者： Qun Wang Feng Zhu Xiang Li Ruida Ye Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Faculty of Computer Science and Engineering Northeastern University Shenyang China Department of Aerospace Engineering and Technology Space Engineering University Beijing China

The prevailing referring expression comprehension (REC) method is based on two stages: 1) detecting multiple candidate proposals using an object detector and 2) aligning proposals with text descriptions. Existing two-stage models have achieved significant improvements with excellent alignment modules. However, their alignment modules treat each proposal equally without filtering expression-unrelated proposals. These expression-unrelated proposals may interfere with the alignment modules’ ability to accurately reason about the target proposal. These proposals also increase the difficulty of training alignment modules. To solve this problem, we propose a new framework, that can suppress expression-unrelated proposals for alignment modules. Specifically, we first design a suppression module, which calculates the relevance scores between the proposals and the expression by using the semantics in the expression. Then, these scores are integrated into three basic alignment modules, including subject, location, and relationship modules, to guide each module to focus on the expression-related proposals. We conduct extensive experiments on three benchmark datasets, and the results show the effectiveness of our suppression module and performance improvement.

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Validation of missile simulation model based on bayesian theory with extreme small sample 3

Validation of missile simulation model based on bayesian the...

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3rd International Conference on Electron Device and Mechanical Engineering, ICEDME 2020

作者： Dai, Zhiwei Wei, Hongkui Li, Xu Lv, Meibo College of Astronautics Northwestern Polytechnical University Xi'an China Beijing Institute of Electronic System Engineering Line 2: Name of Organization Acronyms Acceptable Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing China

ISBN: (纸本)9781728181455

The cost of weapons and equipment, such as high-precision guided missiles, is high to manufacture, and the cost of live-fire launch test is also high. So the number of test data samples is very small, which cannot meet the sample capacity requirements of classic statistical methods. Therefore, this paper proposes a Bayes parameter estimation method based on Grey prediction Model and Bootstrap method (GM-Bootstrap), and it is applied to the simulation model validation under extreme small sample test. First, the Grey prediction Model (GM) is used to expand the extreme small sample, then the Bayes Bootstrap method is used to obtain the parameter distribution, and then the Bayes parameter estimation method is used to obtain the estimation of the unknown parameter. Finally, the simulation model validation under the extreme small sample test was completed through hypothesis testing. The credibility of the method is verified through an example, and a new method is provided for the costly validation of weapon equipment models. © 2020 IEEE.

关键词： Parameter estimation

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Adaptive position tracking control of the lower limb exoskeleton robot with an uncertain dynamic model

Adaptive position tracking control of the lower limb exoskel...

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IEEE Conference on Industrial electronics and Applications (ICIEA)

作者： Ting Yuan Chi Zhang Feng Yi Pingping Lv Shupei Li Meitong Zhang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Instituteof Materials Technology and Engineering Chinese Academy of Sciences Ningbo China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Ningbo China School of Electrical Engineering Hebei University of Science and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

In this paper, an adaptive position control method combining proportional-derivative (PD) control, RBF neural network-based sliding mode (SM) control, and feedforward (FF) control, i.e., PD-FF-SM control, is proposed to deal with the dynamic uncertainties, disturbances, and slow response in lower limb exoskeleton robot system. The Lagrange method is utilized to establish dynamic models that ignore the uncertainties and disturbances in the swing phase and supporting phase. Then, the PD feedback controller is designed with a sliding surface function, to keep the system stable. The FF controller is adopted to improve the response by using dynamic models. And the RBF neural network-based SM controller is designed to compensate for the uncertainties and disturbances. The system’s stability is verified by Lyapunov’s theorem. The simulation results show that the proposed control method can effectively reduce the error of position tracking and response time with inaccurate dynamic modeling.

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BoW3D: Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM

arXiv

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arXiv 2022年

作者： Cui, Yunge Chen, Xieyuanli Zhang, Yinlong Dong, Jiahua Wu, Qingxiao Zhu, Feng Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China The College of Intelligence Science and Technology National University of Defense Technology Changsha China

Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved great success in loop closure. The BoW features for loop searching can also be used in the subsequent 6-DoF loop correction. However, for 3D LiDAR SLAM, the state-of-the-art methods may fail to effectively recognize the loop in real time, and usually cannot correct the full 6-DoF loop pose. To address this limitation, we present a novel Bag of Words for real-time loop closing in 3D LiDAR SLAM, called BoW3D. Our method not only efficiently recognizes the revisited loop places, but also corrects the full 6-DoF loop pose in real time. BoW3D builds the bag of words based on the 3D LiDAR feature LinK3D, which is efficient, pose-invariant and can be used for accurate point-to-point matching. We furthermore embed our proposed method into 3D LiDAR odometry system to evaluate loop closing performance. We test our method on public dataset, and compare it against other state-of-the-art algorithms. BoW3D shows better performance in terms of F1 max and extended precision scores on most scenarios. It is noticeable that BoW3D takes an average of 48 ms to recognize and correct the loops on KITTI 00 (includes 4K+ 64-ray LiDAR scans), when executed on a notebook with an Intel Core i7 @2.2 GHz processor. We release the implementation of our method here: https://***/YungeCui/BoW3D. © 2022, CC BY.

关键词： Optical radar

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Semi-global Periodic Event-triggered Output Regulation for Nonlinear Multi-agent Systems

arXiv

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arXiv 2022年

作者： Zheng, Shiqi Shi, Peng Zhang, Huiyan the School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China the School of Electrical and Electronic Engineering The University of Adelaide AdelaideSA5005 Australia the College of Engineering and Science Victoria University MelbourneVIC8001 Australia the National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing400067 China

This study focuses on periodic event-triggered (PET) cooperative output regulation problem for a class of nonlinear multi-agent systems. The key feature of PET mechanism is that event-triggered conditions are required to be monitored only periodically. This approach is beneficial for Zeno behavior exclusion and saving of battery energy of onboard sensors. At first, new PET distributed observers are proposed to estimate the leader information. We show that the estimation error converges to zero exponentially with a known convergence rate under asynchronous PET communication. Second, a novel PET output feedback controller is designed for the underlying strict feedback nonlinear multi-agent systems. Based on a state transformation technique and a local PET state observer, the cooperative semi-global output regulation problem can be solved by the proposed new control design technique. Simulation results of multiple Lorenz systems illustrate that the developed control scheme is effective. © 2022, CC BY.

关键词： Multi agent systems

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Advances and perspectives on isolation, structural characterization, structure-property relationships, and pharmacological mechanisms of tumor immune glucans: A review

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International journal of biological macromolecules 2025年 315卷 144621页

作者： Yi Tao Lisha Shen Ping Wang College of Pharmaceutical Science Zhejiang University of Technology Hangzhou 310014 PR China Zhejiang Provincial Key Laboratory of TCM for Innovative R&D and Digital Intelligent Manufacturing of TCM Great Health Products PR China. Electronic address: taoyi1985@***. Zhejiang Provincial Key Laboratory of TCM for Innovative R&D and Digital Intelligent Manufacturing of TCM Great Health Products PR China. Zhejiang Provincial Key Laboratory of TCM for Innovative R&D and Digital Intelligent Manufacturing of TCM Great Health Products PR China. Electronic address: wangping45@***.

Tumor immune glucans (TIGs) are emerging as promising anticancer agents capable of enhancing immune responses and mitigating the side effects of chemotherapy. This review analyzes 59 TIGs published between 2015 and 2025, focusing on their isolation, structural characterization, structure-activity relationships, and pharmacological mechanisms. Literature searches were conducted in databases such as Web of Science, PubMed, Google Scholar, Embase, Cochrane Library, *** and CNKI using keywords including "glucans", "tumor immunity", and "polysaccharide structure," covering studies in both English and Chinese. The review highlights the relationship between the structural features of TIGs and their antitumor activities.1,3-linked β-glucans surpassed 1,4-linked or 1,6-linked configurations in antitumor immunostimulatory activity. Elevated molecular weight enhances the structural robustness of TIGs chains, facilitating their selective recognition by cellular receptors and amplifying their anti-tumor immune responses. TIGs exert antitumor effects through mechanisms such as immunomodulation, inhibition of tumor immune escape, and remodeling of the tumor microenvironment, involving signaling pathways such as TLRs/NF-κB, JAK/STAT, MAPK, Bax/Bcl-2, PI3K/Akt, and VEGF/VEGFR. Despite their promising therapeutic potential, challenges remain, including incomplete structural characterization, insufficient IC value data, and a lack of reference drugs. Many studies focus on cytokine levels and cellular activity, but deeper molecular mechanistic insights are needed. Further research into the mechanisms of action and targets of TIGs may pave the way for new cancer treatment strategies.

关键词： Anti-tumor Structure-property relationships Tumor immune glucans

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A Multi-objective optimization model for simulation-based acquisition 7

A Multi-objective optimization model for simulation-based ac...

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7th IEEE International Conference on Progress in Informatics and Computing, PIC 2020

作者： Zhang, Xue Xue, Junjie Zhou, Junhua Shi, Guoqiang Yu, Yan Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China Beijing Simulation Center Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9781728170862

Large-scale equipment presents the characteristics of technology-intensive, knowledge-intensive and complex, which brings high investment and high risk to equipment acquisition. This paper analyzes the various components of equipment acquisition to fully apply modeling and simulation technology to each stage of it. On the basis of multi-objective optimization theory, the objective function of the lowest risk and lowest cost of simulation-based acquisition (SBA) is proposed. Then establishing a multi-objective optimization model for simulation-based acquisition according to the corresponding constraints. The nondominated sorting genetic algorithm II (NSGA II) and multi-objective particle swarm optimization (MOPSO) algorithms are used to optimize the model, and the majority voting method is used for integration. The comparison of simulation examples proves that the multi-objective optimization model oriented to SBA designed in this paper can effectively realize the optimization of each objective of SBA under cost constraints. And the feasibility and efficiency of optimization solution are guaranteed. © 2020 IEEE.

关键词： Multiobjective optimization

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