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42nd Chinese Control Conference, CCC 2023

作者： Zhuang, Chao Xuan, Bo-Kai Xu, Yue-Xuan Ma, Tian-Yi Yin, Ming-Huan Gu, Zhi-Feng Sun, Hao School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin300000 China School of Electrical and Electronic Engineering Shijiazhuang Tiedao University Hebei050043 China Engineering Research Center of Intelligent Rehabilitation Device and Detection Technology Ministry of Education Tianjin300130 China Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Tianjin300401 China

ISBN: (纸本)9789887581543

This paper investigates a variable horizon nonlinear model predictive control strategy based on disturbance observer for a three-degree-of- freedom robot manipulator which has the property of high nonlinearity and uncertainty. Firstly, a nonlinear disturbance observer is implemented to accurately estimate and compensate for uncertain factors such as external disturbances, model parameter disturbance and unmodeled part of the system. Secondly, based on the disturbance observer, the nonlinear model predictive control is utilized to handle the nonlinear model such that avoiding large model error and the predictive horizon of nonlinear model predictive control is improved to the form of dynamic optimization, and the optimal predictive horizon is selected according to the state error of each sampling period. Compared with constant predictive horizon nonlinear model predictive control, this improved strategy not only improves the system tracking performance, but also reduces the use of computing resources and shortens the calculation time. Finally, the numerical simulation and comparative experimental results are presented to verify the superiority and effectiveness of the proposed control strategy. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Flexible manipulators

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Observer-Based Detection and Estimation for UAVs Subject to Remote Signal Attacks and Disturbances

Observer-Based Detection and Estimation for UAVs Subject to ...

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International Conference on Guidance, Navigation and Control, ICGNC 2020

作者： Gu, Yapei Yu, Xiang Guo, Kexin Guo, Lei School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing100191 China

ISBN: (纸本)9789811581540

This paper presents an attack detection and estimation approach to enhance the anti-attack performance for unmanned aerial vehicles (UAVs). The problem of remote signals being tampered by attackers is investigated. First, detect ability of attacks based on authentication signals estimation error is explored. The threshold of the detection mechanism is designed using the upper bound of disturbance. Subsequently, after being detected, the attack model on the control system is established which can further facilitate the attack estimation. Second, attack observer and disturbance observer are designed to estimate attack and disturbance simultaneously. Finally, simulation examples are presented to illustrate the effectiveness of the proposed methods. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Antennas

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Differential Evolution Based Multi-agent Formation Fault Reconstruction

Differential Evolution Based Multi-agent Formation Fault Rec...

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International Conference on Guidance, Navigation and Control, ICGNC 2020

作者： Liao, Zirui Wang, Shaoping Shi, Jian Weng, Qiwang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big-Data Based Precision Medicine Beihang University Beijing100191 China

ISBN: (纸本)9789811581540

The fault reconstruction of second-order multi-agent formation systems under lost communication is studied. Aiming at the specific scenarios of dynamic tracking of multi-agent systems, a mixed-integer programming algorithm based on differential evolution (DE) is proposed according to the characteristics of both continuous kinematic variables and discrete topological variables in the kinematics of UAV formation to ensure the optimization and timeliness. Then, the simulation platform is built and tested in the scene of dynamically tracking. Eventually, the theoretical results are verified by simulation examples. The results show that the method proposed in this paper can ensure that the formation make appropriate adjustments to achieve dynamic target tracking in the process of dynamic target tracking under complex circumstance. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Target tracking

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Multi-Fault Mechanism Analysis And Diagnosis Of Traction Motor In Urban Rail Transit

Multi-Fault Mechanism Analysis And Diagnosis Of Traction Mot...

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2022 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2022

作者： Qiao, Shichang Wang, Shaoping Shi, Jian Liu, Dong Duan, Xiaochuan Wu, Xiao School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang University Beijing100191 China

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

Traction motors for urban rail transit have complex structures, high power-to-weight ratios, and internal coupling of electromagnetic fields, temperature fields and stress fields. If the urban rail transit traction motor enters the fault operation state, the distribution of electromagnetic field, stress field and temperature field will change drastically. This paper analyzes the parameter changes of the urban rail transit traction motor after the occurrence of demagnetization fault, rotor eccentricity fault and short-circuit Fault. D-S evidence theory, wavelet packet energy spectrum and SVM are used to diagnose and classify motor faults. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Traction motors

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CLDG: Contrastive Learning on Dynamic Graphs 39

CLDG: Contrastive Learning on Dynamic Graphs

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39th IEEE International Conference on data engineering, ICDE 2023

作者： Xu, Yiming Shi, Bin Ma, Teng Dong, Bo Zhou, Haoyi Zheng, Qinghua Xi'an Jiaotong University Department of Computer Science and Technology China Xi'an Jiaotong University Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering China Xi'an Jiaotong University Department of Distance Education China Beihang University School of Software China Beihang University Advanced Innovation Center for Big Data and Brain Computing China

ISBN: (纸本)9798350322279

The graph with complex annotations is the most potent data type, whose constantly evolving motivates further exploration of the unsupervised dynamic graph representation. One of the representative paradigms is graph contrastive learning. It constructs self-supervised signals by maximizing the mutual information between the statistic graph's augmentation views. However, the semantics and labels may change within the augmentation process, causing a significant performance drop in downstream tasks. This drawback becomes greatly magnified on dynamic graphs. To address this problem, we designed a simple yet effective framework named CLDG. Firstly, we elaborate that dynamic graphs have temporal translation invariance at different levels. Then, we proposed a sampling layer to extract the temporally-persistent signals. It will encourage the node to maintain consistent local and global representations, i.e., temporal translation invariance under the timespan views. The extensive experiments demonstrate the effectiveness and efficiency of the method on seven datasets by outperforming eight unsupervised state-of-the-art baselines and showing competitiveness against four semi-supervised methods. Compared with the existing dynamic graph method, the number of model parameters and training time is reduced by an average of 2,001.86 times and 130.31 times on seven datasets, respectively. The code and data are available at: https://***/yimingxu24/CLDG. © 2023 IEEE.

关键词： Graph neural networks

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WSpeller: Robust Word Segmentation for Enhancing Chinese Spelling Check

WSpeller: Robust Word Segmentation for Enhancing Chinese Spe...

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2022 Findings of the Association for Computational Linguistics: EMNLP 2022

作者： Li, Fangfang Shan, Youran Duan, Junwen Mao, Xingliang Huang, MinLie School of Computer Science and Engineering Central South University China Institute of Big Data and Internet Innovation Hunan University of Technology and Business China Beijing National Research Center for Information Science and Technology Tsinghua University China

Chinese spelling check (CSC) detects and corrects spelling errors in Chinese texts. Previous approaches have combined character-level phonetic and graphic information, ignoring the importance of segment-level information. According to our pilot study, spelling errors are always associated with incorrect word segmentation. When appropriate word boundaries are provided, CSC performance is greatly enhanced. Based on these findings, we present WSpeller, a CSC model that takes into account word segmentation. A fundamental component of WSpeller is a W-MLM, which is trained by predicting visually and phonetically similar words. Through modification of the embedding layer's input, word segmentation information can be incorporated. Additionally, a robust module is trained to assist the W-MLM-based correction module by predicting the correct word segmentations from sentences containing spelling errors. We evaluate WSpeller on the widely used benchmark datasets SIGHAN13, SIGHAN14, and SIGHAN15. Our model is superior to state-of-the-art baselines on SIGHAN13 and SIGHAN15 and maintains equal performance on SIGHAN14. © 2022 Association for Computational Linguistics.

关键词： Errors

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Model Based Quadriceps Activation Strategy in Squat Training with Exhaustion Method Under Different Loads

Model Based Quadriceps Activation Strategy in Squat Training...

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International Symposium on Computer science and Intelligent Controls (ISCSIC)

作者： Cong Xie Xin Guo Botao Qie School of Artificial Intelligence and Data Science Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology Tianjin China

ISBN: (数字)9798350380286

ISBN: (纸本)9798350380293

The aim of this study is to explore the muscle activation strategy of quadriceps muscle training in untrained sedentary people under different resistance training to exhaustion to provide control target for body state-based intelligence exercise equipment. Ten daily sedentary men with no training experience performed three sets of heavy load squats (single leg bench squat) in exhaustion mode (4RM) and one set of lower resistance squats (double leg squat with 10 KG garment) in exhaustion mode (18-26RM) to explore which and when the muscle fibers will be recruited as much as more. EMG signals from the dominant side of the vastus medialis), rectus femoris, and vastus lateralis in both squats were recorded, and the maximum RMS of 500 MS length in each movement was normalized to the maximum voluntary isometric contraction. Reliability analysis of the normalized EMG signal for each muscle between the three groups of heavy-load squats was as follows: Alpha (vastus medialis)= 0.885, Alpha (rectus femoris)=0.903, Alpha (vastus lateralis) = 0.925. Paired samples t-test of the three muscles under different resistance:p (vastus medialis) <0.001, p (rectus femoris) < 0.001, p (vastus lateralis) < 0.001. The EMG amplitude plateau occurred at the second or third times of heavy load exhaustion groups. The EMG amplitude plateau occurred in 53%-61% of exhaustion times in the lower resistance group. In conclusion, for quadriceps muscle training, 1) Muscle fibers activated by exhaustive training with small resistance are less than those activated by heavy weight training. 2) Quadriceps strength training, all muscle fibers can be activated before reaching the exhaustion number.

关键词： Training Legged locomotion Resistance Muscles Motors Electromyography Optical fiber devices Reliability Immune system Load modeling

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Towards understanding structure–property relations in materials with interpretable deep learning

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npj Computational Materials 2023年第1期9卷 157-168页

作者： Tien-Sinh Vu Minh-Quyet Ha Duong-Nguyen Nguyen Viet-Cuong Nguyen Yukihiro Abe Truyen Tran Huan Tran Hiori Kino Takashi Miyake Koji Tsuda Hieu-Chi Dam Japan Advanced Institute of Science and Technology NomiIshikawaJapan HPC SYSTEMS Inc. MinatoTokyoJapan Applied Artificial Intelligence Institute Deakin UniversityGeelongVICAustralia School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGAUSA Research and Services Division of Materials Data and Integrated System National Institute for Materials ScienceTsukubaIbarakiJapan Research Center for Computational Design of Advanced Functional Materials National Institute of Advanced Industrial Science and TechnologyTsukubaIbarakiJapan Department of Computational Biology and Medical Sciences Graduate School of Frontier SciencesUniversity of TokyoKashiwa-shiChiba-kenJapan International Center for Synchrotron Radiation Innovation Smart(SRIS) Tohoku UniversityAoba-kuSendaiJapan

Deep learning(DL)models currently employed in materials research exhibit certain limitations in delivering meaningful information for interpreting predictions and comprehending the relationships between structure and material *** address these limitations,we propose an interpretable DL architecture that incorporates the attention mechanism to predict material properties and gain insights into their structure–property *** proposed architecture is evaluated using two well-known datasets(the QM9 and the Materials Project datasets),and three in-house-developed computational materials ***–test–split validations confirm that the models derived using the proposed DL architecture exhibit strong predictive capabilities,which are comparable to those of current state-of-the-art ***,comparative validations,based on first-principles calculations,indicate that the degree of attention of the atoms’local structures to the representation of the material structure is critical when interpreting structure–property relationships with respect to physical *** properties encompass molecular orbital energies and the formation energies of *** proposed architecture shows great potential in accelerating material design by predicting material properties and explicitly identifying crucial features within the corresponding structures.

关键词： properties property structure

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Enhancing Encrypted Internet Traffic Classification Through Advanced data Augmentation Techniques

arXiv

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arXiv 2024年

作者： Zion, Yehonatan Aharon, Porat Dubin, Ran Dvir, Amit Hajaj, Chen Department of Computer Science Ariel Cyber Innovation Center Ariel University Israel Dept. of Computer and Software Eng. Ariel Cyber Innovation Center Ariel University Israel Department of Industrial Engineering and Management Data Science Artificial Intelligence Research Center Ariel University Israel

The increasing popularity of online services has made Internet Traffic Classification a critical field of study. However, the rapid development of internet protocols and encryption limits usable data availability. This paper addresses the challenges of classifying encrypted internet traffic, focusing on the scarcity of open-source datasets and limitations of existing ones. We propose two data Augmentation (DA) techniques to synthetically generate data based on real samples: Average augmentation and MTU augmentation. Both augmentations are aimed to improve the performance of the classifier, each from a different perspective: The Average augmentation aims to increase dataset size by generating new synthetic samples, while the MTU augmentation enhances classifier robustness to varying Maximum Transmission Units (MTUs). Our experiments, conducted on two well-known academic datasets and a commercial dataset, demonstrate the effectiveness of these approaches in improving model performance and mitigating constraints associated with limited and homogeneous datasets. Our findings underscore the potential of data augmentation in addressing the challenges of modern internet traffic classification. Specifically, we show that our augmentation techniques significantly enhance encrypted traffic classification models. This improvement can positively impact user Quality of Experience (QoE) by more accurately classifying traffic as video streaming (e.g., YouTube) or chat (e.g., Google Chat). Additionally, it can enhance Quality of Service (QoS) for file downloading activities (e.g., Google Docs). © 2024, CC BY-NC-ND.

关键词： Quality of service

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An improved reconfigurable logic in resistive random access memory

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Integration 2022年 87卷 169-175页

作者： Zhao, Yi Chen, Hui Liu, Peng Wu, Jigang Luo, Dongxiang The Center for High Performance Computing and Data Science School of Computer Science and Technology Guangdong University of Technology Guangdong510006 China School of Chemistry and Chemical Engineering/Institute of Clean Energy and Materials/Guangzhou Key Laboratory for Clean Energy and Materials/Huangpu Hydrogen Innovation Center Guangzhou University Guangzhou510006 China Institute of Semiconductors South China Normal University Guangzhou510631 China

Emerging non-volatile devices have shown great potential in computing in-memory (CIM). This work proposes a logic design method based on the complementary resistance switching (CRS) structure, which is connected by two anti-serially memristors. Three logics including AND, OR, and NIMP can be implemented in one step. Moreover, XOR logic can be implemented in two steps. Based on the proposed design, a 1-bit full adder is implemented with the fewer number of memristors and operation steps compared with existing works. The feasibility and correctness of our design are verified by the SPICE simulations with the Voltage Threshold Adaptive Memristor (VTEAM) model. In addition, we evaluate the ISCAS’85 benchmark circuit based on the proposed logic. Compared with existing methods, the performance and area overhead have been improved by the proposed method. © 2022 Elsevier B.V.

关键词： Memristors

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