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EmotionIC: emotional inertia and contagion-driven dependency modeling for emotion recognition in conversation

science China(Information sciences) 2024年第8期67卷 130-146页

作者： Yingjian LIU Jiang LI Xiaoping WANG Zhigang ZENG School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education Institute of Artificial Intelligence Huazhong University of Science and Technology

Emotion recognition in conversation(ERC) has attracted growing attention in recent years as a result of the advancement and implementation of human-computer interface technologies. In this paper,we propose an emotional inertia and contagion-driven dependency modeling approach(EmotionIC) for ERC tasks. Our EmotionIC consists of three main components, i.e., identity masked multi-head attention(IMMHA), dialogue-based gated recurrent unit(DiaGRU), and skip-chain conditional random field(SkipCRF).Compared to previous ERC models, EmotionIC can model a conversation more thoroughly at both the feature-extraction and classification levels. The proposed model attempts to integrate the advantages of attention-and recurrence-based methods at the feature-extraction level. Specifically, IMMHA is applied to capture identity-based global contextual dependencies, while Dia GRU is utilized to extract speaker-and temporal-aware local contextual information. At the classification level, SkipCRF can explicitly mine complex emotional flows from higher-order neighboring utterances in the conversation. Experimental results show that our method can significantly outperform the state-of-the-art models on four benchmark *** ablation studies confirm that our modules can effectively model emotional inertia and contagion.

关键词： emotion recognition in conversation emotional inertia and contagion multi-head attention gated recurrent unit conditional random field

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Feedback Generative Adversarial Network With Channel-space Attention for Image-Based Optimal Path Search Planning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4293-4307页

作者： Sun, Tao Li, Jian-Sheng Zhang, Yi-Fan Ru, Xin-Feng Wang, Ke Tsinghua University Department of Automation Beijing100084 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tongji University School of Economics and Management Shanghai200092 China

Path planning and seeking is one of the most challenging and interesting problems in the field of artificial intelligence. In this article, we propose a new image-based path planning algorithm to overcome traditional design concepts based on complex topological networks. Specifically, a novel feedback generative adversarial network learning model with channel-space attention (CSA-FGAN) is developed to search and plan an optimal path. It is worth noting that the input and output of the proposed feedback learning model are RGB images with complex spatial obstacle environment maps and RGB images with feasible paths, respectively. In particular, in order to further enhance the feature extraction ability and path prediction accuracy of image data, the feedback attention mechanism controls and improves the depth of the network by forming a closed loop of the proposed learning model. Final, three application scenario image examples are conducted to verify the superiority of the proposed path planning policy. © 2020 IEEE.

关键词： Motion planning

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Reinforcement Learning control for Hypersonic Morphing Flight Vehicle with Identification of Dynamic Parameter

Reinforcement Learning Control for Hypersonic Morphing Fligh...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Nie, Ying Zhang, Yuan Bai, Wenyan Cao, Yuteng Yu, Chunmei Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing100854 China

ISBN: (纸本)9789811966125

A reinforcement learning (RL) controller with identification of the dynamic parameter of hypersonic morphing flight vehicle (HMFV) is proposed in this paper, successfully realizing the end-to-end control of attack angle in the longitudinal plane. The following improvements are made in this paper: Firstly, the dynamic parameter (rudder efficiency coefficient) of the flight vehicle is added into the state vector, so that the RL controller can understand the control ability of the rudder and generates the optimal control commands in the current state. Secondly, five instead of only one consecutive attack angle deviations are used to jointly generate the state vector, which enables the RL controller to use the model state information of the previous period of time and improve the control stability. Three simulations are set up in this paper. The simulation results show that the RL controller proposed in this paper can achieve stable and high precision attack angle control under large-scale environmental deviations and has strong generalization under different guidance commands. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Generation of Sub-Nanosecond Microwave Pulse with High Compression Factor Using Reflection Structure

Generation of Sub-Nanosecond Microwave Pulse with High Compr...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Zhang, Zhiyuan Pan, Ruoyang Wang, Weijie Wu, Zhiqiang Liu, Guo Yao, Yelei Jiang, Wei Wu, Zeiwei Wang, Jianxun Luo, Yong School of Integrated Circuit Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

ISBN: (纸本)9798350375909

This paper presents a method of generating sub-nanosecond microwave pulses with a high compression factor using a reflection structure. This method can reduce the length of the compressor and has a high compression factor, which can further enhance the power level of broadband vacuum electron amplifiers. In the experiment, a microwave pulse with a duration of 0.257 ns and a high compression factor of 43.3 is generated. The experiment is in good agreement with our theory and simulation. © 2024 IEEE.

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State estimation for delayed switched positive systems: delayed radius approach

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science China(Information sciences) 2024年第8期67卷 190-205页

作者： Weizhong CHEN Zhongyang FEI Xudong ZHAO Zheng-Guang WU School of Electronics and Information Xi'an Polytechnic University Research Institute of Intelligent Control and Systems Harbin Institute of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of Control Science and Engineering Dalian University of Technology State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University

In this paper, an interval estimation scheme is developed for delayed switched positive systems（DSPS） with mode-dependent average dwell time switching. A lossless zonotopic estimation approach is proposed for the delayed intersection zonotope with the positive generator matrix. First, considering the existence of asynchronism between the system mode and the correction matrix mode, the mismatched intersection zonotope is constructed for DSPS to verify the consistency between the system model and ***, by utilizing the introduced radius definitions, the ?∞performance is addressed to optimize the size of delayed intersection zonotopes. Subsequently, we present a joint-design approach of switching signals and the mode-dependent correction matrix by constructing positive generator matrix-based delayed radius functions. Furthermore, guaranteed nonnegative state bounds are derived for the considered DSPS based on the proposed lossless zonotopic estimation criteria. Finally, detailed simulations are conducted to validate the feasibility and superiority of the developed methods.

关键词： delayed switched positive systems interval estimation asynchronous correction matrix zonotopes mode-dependent average dwell time

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Adaptive modification of turbofan engine nonlinear model based on LSTM neural networks and hybrid optimization method

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Chinese Journal of Aeronautics 2022年第9期35卷 314-332页

作者： Yanhua MA Xian DU Ximing SUN School of Microelectronics Dalian University of TechnologyDalian 116024China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of EducationDalian University of TechnologyDalian 116024China School of Control Science and Engineering Dalian University of TechnologyDalian 116024China

An accurate and reliable turbofan engine model which can describe its dynamic behavior within the full flight envelop and lifecycle plays a critical role in performance optimization, controller design and fault diagnosis. However, due to the performance differences caused by the tolerance of engine manufacturing and assembly, and performance degradation during continuously stringent environmental regulations, the model accuracy is severely reduced. In this paper, an adaptive modification method of turbofan engine nonlinear Component-Llevel Model(CLM) based on Long Short-Term Memory(LSTM) Neural Network(NN) and hybrid optimization algorithm is pro-posed. First, a dynamic compensator with a combined LSTM NN architecture is constructed to compensate for the initial error between the experimental data and CLM of a turbofan engine under health condition. Then, a sensitivity analysis approach based on the entropy coefficient and technique for order preference by similarity to an ideal solution integrated evaluation is developed to choose the unmeasurable health parameters to be adjusted. Finally, a parallel hybrid optimization algorithm is developed to complete the adaptive model modification when the performance degrades. The proposed method is verified on a military low-bypass twin-spool turbofan engine, and the experimental results show the effectiveness of the proposed method.

关键词： Hybrid optimization Long short-term memory Model modification and testing Sensitivity analysis Turbofan engines

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Large flexible structure vibration measurement based on machine vision

Large flexible structure vibration measurement based on mach...

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第43届中国控制会议

作者： Yuanyuan Zhu Haibo Zhang Zhijie Ning Yanning Guo Lingxi Zheng Harbin Institute of Technology National Key Laboratory of Space Intelligent Control

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

A multi-target synchronous measurement method is proposed for the vibration measurement problem of large flexible structures. Select the appropriate system hardware according to the actual measurement requirements, and the binocular camera is used to acquire the image sequence of multiple points during the vibration process. An innovative method is proposed that combines feature point matching and Maximum Intersection over Union is proposed to achieve one-to-one mapping between multiple points. The vibration information of the flexible structure is obtained by image processing and three-dimensional coordinate calculation. Compared with the results obtained by the Optitrack motion capture *** vibration with a frequency of 3Hz, the relative errors of most measurements are within 5%, which meets the requirements of most vibration measurements.

关键词： Machine vision Flexible structure Multi-points matching Digital image processing SIFT IoU

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MG6D: A Deep Fusion Approach for 6D Pose Estimation with Mamba and Graph Convolution Network

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IEEE Access 2025年 13卷 100433-100445页

作者： Zhu, Jiaqi Li, Bin Zhao, Xinhua Tianjin University of Technology School of Computer Science and Engineering Tianjin 300384 China Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin 300384 China

Accurate and efficient 6D pose estimation is a fundamental technology in many industrial applications. While existing dense correspondence methods have shown progress, they face challenges in multimodal feature fusion under complex scenarios involving occlusions, illumination variations, and sensor noise. This paper proposes a novel 6D pose estimation framework that addresses these limitations through a hybrid Mamba-Graph architecture. The algorithm first introduces a panoramic attention fusion Mamba module, leveraging state-space modeling to capture long-range dependencies in multi-modal data while establishing cross-dimensional interactions between channel and spatial features to emphasize critical information. A dynamic graph convolutional adaptive fusion module is then designed to enable cross-modal geometric consistency modeling via multi-modal feature integration. Finally, a texture-geometry co-driven keypoint selection mechanism is proposed to ensure keypoint distributions satisfy both spatial uniformity and discriminability requirements. Experimental results on three common datasets demonstrate that the proposed algorithm achieves ADD(-S) metrics of 99.82%, 80.26%, and 97.2%, respectively. Notably, it exhibits significant advantages in pose estimation for objects with repetitive textures and high symmetry. © 2013 IEEE.

关键词： 6D pose estimation fusion mamba graph feature fusion panoramic attention

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Robust Target Detection and Localization for UAV Autonomous Landing with Partially Occluded Targets 15th

Robust Target Detection and Localization for UAV Autonomous ...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Shao, Mingmei Liu, Yanyan Tang, Jiaze Liu, Huanyu Li, Junbao Faculty of Computing Harbin Institute of Technology Harbin150080 China National Key Laboratory of Electromagnetic Space Security Tianjin300308 China Electrical Measurement Technology and Intelligent Control Institute School of Instrumentation Science and Engineering Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9789819700677

This paper presents an approach for robust target detection and localization in the context of UAV autonomous landing with partially occluded targets. Since the performance of the autonomous landing system largely depends on the accurate detection and positioning of the landing target, it is very important to deal with the local occlusion caused by obstacles or environmental factors. In order to improve the overall performance of the system, we propose a fault-tolerant target detection method and target completion strategy. The proposed target detection method combines image processing technology with feature extraction algorithm, which can recognize and locate the landing target even in the case of occlusion. The target completion strategy aims to recover the missing part of the occluded target and make the detection and location algorithm execute more reliably. We perform experiments on image data sets with different horizontal object occlusion to evaluate the performance of the proposed method. The results show that our method successfully detects and locates the landing target under different occlusion levels, and significantly improves the performance of UAV autonomous landing system in the real scene. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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A Ku-band Compact High-power Sheet Beam Extended Interaction Oscillator 16

A Ku-band Compact High-power Sheet Beam Extended Interaction...

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16th UK-Europe-China Workshop on Millimetre Waves and Terahertz Technologies, UCMMT 2023

作者： Zhao, Wen Wang, Jianxun Li, Xinjie Jiang, Wei Li, Hao Luo, Yong University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu China University of Electronic Science and Technology of China Laboratory of Electromagnetic Space Cognition and Intelligent Control Chengdu China

ISBN: (纸本)9798350339406

A compact sheet beam extended interaction oscillator (SBEIO) with frequency of 13.986 GHz is proposed in this paper. The model adopts a ladder structure with six gaps and operates in the TM11-2π mode. By optimizing the structure through the MATLAB program of the nonlinear theoretical simulation designed in our group, the efficiency is increased from 23.6% to 32.1%. The voltage and current of the electron beam are respectively 45 kV, 14 A. The current density remains at 50 A/cm2, which is suitable for the application of the periodic permanent magnet and beneficial for compact overall structure. The output power reaches 157 KW. © 2023 IEEE.

关键词： MATLAB

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