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arXiv 2024年

作者： Wang, Ziwei Li, Siyang Wu, Dongrui Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

Epilepsy significantly impacts global health, affecting about 65 million people worldwide, along with various animal species. The diagnostic processes of epilepsy are often hindered by the transient and unpredictable nature of seizures. Here we propose a multi-space alignment approach based on cross-species and cross-modality electroencephalogram (EEG) data to enhance the detection capabilities and understanding of epileptic seizures. By employing deep learning techniques, including domain adaptation and knowledge distillation, our framework aligns cross-species and cross-modality EEG signals to enhance the detection capability beyond traditional within-species and within-modality models. Experiments on multiple surfaces and intracranial EEG datasets of humans and canines demonstrated substantial improvements in detection accuracy, achieving over 90% AUC scores for cross-species and cross-modality seizure detection with extremely limited labeled data from the target species/modality. To our knowledge, this is the first study that demonstrates the effectiveness of integrating heterogeneous data from different species and modalities to improve EEG-based seizure detection performance. This is a pilot study that provides insights into the challenges and potential of multi-species and multi-modality data integration, offering an effective solution for future work to collect huge EEG data to train large brain models. © 2024, CC BY.

关键词： Electroencephalography

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Niobium telluride absorber for a mode-locked vector soliton fiber laser

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Science China(Physics,Mechanics & Astronomy) 2023年第5期66卷 130-138页

作者： XinXin Shang NanNan Xu Jia Guo Shuo Sun HuaNian Zhang SWageh Ahmed AAl-Ghamdi Han Zhang DengWang Li Shandong Province Key Laboratory of Medical Physics and Image Processing Technology Shandong Provincial Key Laboratory of Optics and Photonic DeviceSchool of Physics and ElectronicsShandong Normal UniversityJinan 250014China Institute of Microscale Optoelectronics Collaborative Innovation Center for Optoelectronic Science&TechnologyKey Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong ProvinceCollege of Physics and Optoelectronic EngineeringShenzhen Key Laboratory of Micro-Nano Photonic Information TechnologyGuangdong Laboratory of Artificial Intelligence and Digital Economy(SZ)Shenzhen UniversityShenzhen 518060China School of Physics and Optoelectronic Engineering Shandong University of TechnologyZibo 255049China Department of Physics Faculty of ScienceKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Niobium telluride(NbTe_(2)),an emerging transition metal dichalcogenide material,has been theoretically predicted to have nonlinear absorption properties and excellent optical ***,only a few studies of the utilization of NbTe_(2)in ultrafast photonics have been *** this work,a NbTe_(2)-based saturable absorber(SA)was applied in an erbium-doped fiber as a mode-locked device,and a vector soliton based on NbTe_(2)was obtained for the first ***_(2)-PVA film SA was successfully prepared by the liquid-phase exfoliation and spin coating methods,with a modulation depth of up to 10.87%.The nonlinear absorption coefficient of NbTe_(2)-based SA film tested through the open-aperture Z-scan laser measurement is 0.62×10^(−11) m/W.A conventional soliton with a pulse duration of 858 fs was generated using NbTe_(2)-based SA,which was demonstrated to be a kind of polarization-locked vector soliton in further *** experimental results reveal the nonlinear optical properties of NbTe_(2)and broaden its applications in ultrafast photonic devices.

关键词： niobium telluride saturable absorber mode-locked pulse fiber laser

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GPC-LIO-SAM:Lidar inertial odometry and mapping method for mobile robot with ground plane constraint

GPC-LIO-SAM:Lidar inertial odometry and mapping method for m...

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第43届中国控制会议

作者： Chong Cao Gang Peng Dingxin He Yihao Cao Yue Xu Zhang Deng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Engineering Research Center of Autonomous Intelligent Unmanned Systems Ministry of Education Wuhan Lisai Technology Co. Ltd.

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Due to the limitation of the vertical angle resolution of the lidar sensor,the observation information in the vertical direction is reduced,resulting in the elevation cumulative drift phenomenon of many lidar SLAM algorithms in large-scale environment,which reduces the accuracy of pose estimation and the quality of *** order to solve this problem,based on LIO-SAM,this paper proposes a lidar SLAM algorithm with ground plane *** method can effectively extract the ground point cloud and obtain the plane normal vector,and construct the constraint relationship with the prior plane normal *** optimal state estimation is solved by nonlinear optimization method,which effectively reduces the elevation drift caused by the long-term operation of the system in large-scale *** paper compares the improved algorithm with A-LOAM,LeGO-LOAM and original LIO-SAM algorithms in challenging datasets such as KITTI,M2 DGR and *** results show that this method effectively improves the accuracy of pose estimation and the quality of mapping,and limit the elevation drift of mobile robot in ground operation,which has high application value.

关键词： Ground plane constraint elevation drift LIDAR simultaneous localization and mapping(SLAM)

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Temperature Gradient Analyses of a Tubular Solid Oxide Fuel Cell Fueled by Methanol

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Transactions of Tianjin University 2023年第1期29卷 14-30页

作者： Qidong Xu Meiting Guo Lingchao Xia Zheng Li Qijiao He Dongqi Zhao Keqing Zheng Meng Ni Department of Building and Real Estate Research Institute for Sustainable Urban Development(RISUD)&Research Institute for Smart Energy(RISE)The Hong Kong Polytechnic UniversityHong Kong 999077China School of Artifi cial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074China School of Low-Carbon Energy and Power Engineering China University of Mining and TechnologyXuzhou 221116China

Thermal management in solid oxide fuel cells(SOFC)is a critical issue due to non-uniform electrochemical reactions and convective fl ows within the ***,a 2D mathematical model is established herein to investigate the thermal responses of a tubular methanol-fueled *** show that unlike the low-temperature condition of 873 K,where the peak temperature gradient occurs at the cell center,it appears near the fuel inlet at 1073 K because of the rapid temperature rise induced by the elevated current *** the large heat convection capacity,excessive air could not eff ectively eliminate the harmful temperature gradient caused by the large current ***,optimal control of the current density by properly selecting the operating potential could generate a local thermal neutral ***,the maximum axial temperature gradient could be reduced by about 18%at 973 K and 20%at 1073 K when the air with a 5 K higher temperature is ***,despite the higher electrochemical performance observed,the cell with a counter-fl ow arrange-ment featured by a larger hot area and higher maximum temperature gradients is not preferable for a ceramic SOFC system considering thermal ***,this study could provide insightful thermal information for the operating condition selection,structure design,and stability assessment of realistic SOFCs combined with their internal reforming process.

关键词： Solid oxide fuel cell Modeling Methanol fuel Temperature gradient Internal reforming

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Active Compliance Variable Impedance Control of Lower Supernumerary Robotic Limb*

Active Compliance Variable Impedance Control of Lower Supern...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Jun Huo Xinyi Wang Bo Yang Qingyang Yan Zhaofan Yuan Jian Huang Hubei Key Laboratory of Brain-inspired Intelligent Systems and the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China China Telecom Research Institute Guangdong China China Ship Development and Design Centre Wuhan China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

In human-robot systems, ensuring user safety amidst external disturbances remains paramount. An efficient variable impedance control (VIC) technique is designed to enhance human-robot interaction, particularly in scenarios with external force disturbances. By dynamically adapting impedance parameters in response to detected changes in contact force, VIC achieves heightened system flexibility. The robust stability of the VIC system is rigorously established using the Lyapunov approach, with a parameter update law tailored for a lower limb supernumerary robotic limb robot. Through simulations and experiments, the efficacy of the system in maintaining a specific safety margin is demonstrated. Moreover, the technique offers a pragmatic solution to accommodate individual variations in walking gait and cross-user disparities in interaction. The proposed method contributes to advancing the safety and adaptability of cross-user human-robot systems.

关键词： Legged locomotion Adaptation models Mechatronics Robust stability Force Human-robot interaction Safety Impedance Robots Pragmatics

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Composite Learning Attitude Consensus for Multi-Quadrotor systems with Parametric Uncertainties

Composite Learning Attitude Consensus for Multi-Quadrotor Sy...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Zhou, Yan Wen, Guanghui Nie, Jing Nan, Xiaoya School of Cyber Science and Engineering Southeast University Nanjing China Southeast University Department of Systems Science Nanjing China Satellite Information Intelligent Processing and Application Research Laboratory Beijing China School of Artificial Intelligence Nanjing University of Information Science & Technology Nanjing China

ISBN: (纸本)9798350316308

This article investigates the attitude consensus of multi-quadrotor systems subject to parametric uncertainties. Some special auxiliary variables are given to construct the tracking errors. By integrating composite learning into backstepping control, a team of distributed adaptive controllers are established. In composite learning, tracking errors and prediction errors are used for designing parameter adaptive laws, where prediction errors are generated by the integrals of auxiliary variables over moving time intervals. It is shown that under some interval exci-tation conditions that are much weaker than persistent excitation conditions, the exponential convergence of parameter estimation errors and tracking errors can be realized, as well as the attitude consensus. Finally, the validity of the presented control scheme is demonstrated by performing numerical simulations. © 2023 IEEE.

关键词： Errors

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Machine learning predicts long-term mortality after acute myocardial infarction using systolic time intervals and routinely collected clinical data

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intelligent Medicine 2024年第3期4卷 170-176页

作者： Bijan Roudini Boshra Khajehpiri Hamid Abrishami Moghaddam Mohamad Forouzanfar Department of Systems Engineering School of Advanced TechnologyUniversity of QuebecMontrealCanada Machine Vision and Medical Image Processing(MVMIP)Laboratory Faculty of Electrical and Computer EngineeringK.N.Toosi University of TechnologyTehranIran Research Center of the Montreal University Institute of Geriatrics MontrealCanada

Background Precise estimation of current and future comorbidities of patients with cardiovascular disease is an important factor in prioritizing continuous physiological monitoring and new *** learning(ML)models have shown satisfactory performance in short-term mortality prediction in patients with heart disease,whereas their utility in long-term predictions is *** study aimed to investigate the performance of tree-based ML models on long-term mortality prediction and effect of two recently introduced biomarkers on long-term *** This study used publicly available data from the Collaboration Center of Health Information Appli-cation at the Ministry of Health and Welfare,Taiwan,*** collected data were from patients admitted to the cardiac care unit for acute myocardial infarction(AMI)between November 2003 and September *** collected and analyzed mortality data up to December *** records were used to gather demo-graphic and clinical data,including age,gender,body mass index,percutaneous coronary intervention status,and comorbidities such as hypertension,dyslipidemia,ST-segment elevation myocardial infarction,and non-ST-segment elevation myocardial *** the data,collected from 139 patients with AMI,from medical and demographic records as well as two recently introduced biomarkers,brachial pre-ejection period(bPEP)and brachial ejection time(bET),we investigated the performance of advanced ensemble tree-based ML algorithms(random forest,AdaBoost,and XGBoost)to predict all-cause mortality within 14 years.A nested cross-validation was performed to evaluate and compare the performance of our developed models precisely with that of the conventional logistic regression(LR)as the baseline *** The developed ML models achieved significantly better performance compared to the baseline LR(C-Statistic,0.80 for random forest,0.79 for AdaBoost,and 0.78 for XGBoost,vs.0.77 for LR)(PRF<0.001,PAdaBoost<0.001,a

关键词： Electrocardiogram Predication Mortality prediction Machine learning

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Fog images Generation About Unmanned Surface Vessels with Improved Generative Adversarial Network

Fog Images Generation About Unmanned Surface Vessels with Im...

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Chinese Control Conference (CCC)

作者： Yifeng Tang Zhihui Huang Chuancong Tang Chuanshang Luo Yifan Xu Bin Liu Hai-Tao Zhang Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation the Engineering Research Center of Autonomous Intelligent Unmanned Systems Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan China

This paper proposes a fog weather data augmentation method for the unmanned surface vessels (USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided generation of the atmospheric scattering model in this paper. A Laplacian Pyramid Based Depth Residuals model is added to the generator which reduces the difficulty of generating fog images caused by the degradation of water surface image and improves the quality of generated images. Finally, fog images are generated from sunny weather images collected with HUST-12C by LPBDR-GAN model and experiments show that generated images are very close to real fog images.

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A TDOA/AOA Hybrid Positioning Based on Improved Sparrow Search Algorithm for Mobile Position Estimation

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Wireless Communications and Mobile Computing 2023年第1期2023卷

作者： Hu, Zhongyi Lu, Dongwan Xu, Minghai Tong, Yinsheng Ma, Hanjie Yue, Yinggao School of Computer Science and Artificial Intelligence Wenzhou University Wenzhou325035 China Intelligent Information Systems Institute Wenzhou University Wenzhou325035 China Key Laboratory of Intelligent Image Processing and Analysis Wenzhou China School of Intelligent Manufacturing and Electronic Engineering Wenzhou University of Technology Wenzhou325035 China

To address the difficulty in calculating the nonlinear equation of time difference of arrival (TDOA) positioning, as well as the problem of measurement error in the hybrid time difference of arrival/angle of arrival (TDOA/AOA) positioning algorithm, an improved sparrow search algorithm is proposed to optimize positioning, and the optimization mechanism is retained on the basis of improving the performance of the original algorithm. The maximum likelihood estimation method is used to calculate the objective function, and then, the estimated function of the mobile station is used as the fitness function to generate the initial population of sparrows. Then, using particle swarm optimization, optimize the sparrow search algorithm and obtain the population's optimal solution in order to obtain the optimal position. The simulation results show that, when compared to the existing algorithm, increasing the number of base stations increases the average accuracy of the sparrow search algorithm (SSA) positioning method by 18.54% and 4.5%, respectively, and, when compared to the proposed particle swarm optimization (PSO) positioning method, by 13.79% and 11.6% as the radius increases. The SSA hybrid positioning algorithm performs better in terms of positioning accuracy, convergence speed, and robustness. © 2023 Zhongyi Hu et al.

关键词： Time difference of arrival

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SETTP: Style Extraction and Tunable Inference via Dual-Level Transferable Prompt Learning 27

SETTP: Style Extraction and Tunable Inference via Dual-Level...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Jin, Chunzhen Huang, Yongfeng Wang, Yaqi Cao, Peng Zaïane, Osmar Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education Northeastern University Shenyang China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China Amii University of Alberta EdmontonAB Canada

ISBN: (纸本)9781643685489

Text style transfer, an important research direction in natural language processing, aims to adapt the text to various preferences but often faces challenges with limited resources. In this work, we introduce a novel method termed Style Extraction and Tunable Inference via Dual-level Transferable Prompt Learning (SETTP) for effective style transfer in low-resource scenarios. First, SETTP learns source style-level prompts containing fundamental style characteristics from high-resource style transfer. During training, the source style-level prompts are transferred through an attention module to derive a target style-level prompt for beneficial knowledge provision in low-resource style transfer. Additionally, we propose instance-level prompts obtained by clustering the target resources based on the semantic content to reduce semantic bias. We also propose an automated evaluation approach of style similarity based on alignment with human evaluations using ChatGPT-4. Our experiments across three resourceful styles show that SETTP requires only 1/20th of the data volume to achieve performance comparable to state-of-the-art methods. In tasks involving scarce data like writing style and role style, SETTP outperforms previous methods by 16.24%. © 2024 The Authors.

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