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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Wang, Zewen She, Jinhua Sato, Daiki School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China Kanagawa Yokohama226-8503 Japan Tokyo University of Technology School of Engineering Tokyo Hachioji192-0982 Japan

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This paper combines the equivalent-input-disturbance (EID) approach with the sliding-mode control (SMC) approach that improves disturbance-rejection performance. A novel equivalent-input-disturbance (NEID) approach is presented, which considers the disturbance estimation in the state observer. A sliding surface is designed based on the internal model principle, which is called internal-model sliding-mode control (IMSMC). A stability condition is devised for the SMC-EID-based control system. The parameters are designed based on the stability condition. Simulation results show the validity of the NEID approach. © 2022 IEEE.

关键词： Sliding mode control

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An Attention Detection system Based on Gaze Estimation Using Self-supervised Learning 8th

An Attention Detection System Based on Gaze Estimation Usin...

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8th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2023

作者： Zeng, Xiang-Yu Zhang, Bo-Yang Liu, Zhen-Tao School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789819975891

With the rapid development of online education around world, it becomes difficult for teachers to evaluate the effect of learning during the online class. To solve this problem, an attention detection system based on gaze estimation using self-supervised learning is proposed. Self-supervised learning is used to train the gaze estimation network and it achieved an average gaze angle error of 6. 5∘ on the MPIIFaceGaze dataset. Cross dataset testing was performed by 5 test subjects in the RT-GENE dataset and all samples in the Columbia dataset, in which achieved average gaze angle error 13. 8∘ and 5. 5∘. It is found that the network has good cross dataset generalization performance, but it is susceptible to factors such as feature occlusion and low image clarity. Then, we developed an attention detection system which has functions of unmanned detection, eye state detection, and gaze detection. Online classroom experiments were conducted to verify the effectiveness of the proposed method, in which the average accuracy of the detection of distraction is around 60%. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Supervised learning

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Molecular dynamics study of the effects of deposition parameters on Si0.5Ge0.5 film growth on Ge(100) substrate

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Computational Materials Science 2025年 256卷

作者： Xie, Jianan Lin, Tao Wang, Cailin College of Automation and Information Engineering Xi'an University of Technology Xi'an710048 China Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

With the widespread application of SiGe films in the semiconductor field, precisely controlling the growth process to obtain high-quality films has become an important research direction. This study focuses on the growth of Si0.5Ge0.5 films on Ge (100) substrates and investigates the effects of different deposition parameters (such as deposition interval, incident energy, incident angle, and substrate off-angle) on film quality. Through molecular dynamics simulations, the effects of these deposition parameters on the crystal structure, dislocation density, and surface roughness of the films are systematically analyzed. The results show that shorter deposition intervals lead to faster atomic deposition, increasing the proportion of disordered atoms;longer deposition intervals effectively reduce the proportion of disordered atoms, but excessively long intervals may increase surface roughness and form island-like structures. Additionally, appropriate incident energy, incident angle, and substrate off-angle can significantly optimize the film quality, with the surface roughness being minimized when the incident energy is 1 eV. © 2025 Elsevier B.V.

关键词： Crystal atomic structure

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Speech Emotion Recognition Based on Syllable-Level Feature Extraction

SSRN

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SSRN 2023年

作者： Rehman, Abdul Liu, Zhen-Tao Wu, Min Cao, Wei-Hua Jiang, Cheng-Shan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Speech emotion recognition systems have high computational requirements for deep learning models and low generalizability mainly because of the poor reliability of emotional measurements across multiple corpora. To solve these problems, we present a speech emotion recognition system based on a reductionist approach of decomposing and analyzing syllable-level ***-spectrogram of an audio stream is decomposed into syllable-level components, which are then analyzed to extract statistical features. The proposed method uses formant attention, noise-gate filtering, and rolling normalization contexts to decrease contextual differences and increase focus the attention on the structure of a formant. A set of syllable-level formant features is extracted and fed into a single hidden layer neural network that makes predictions for each syllable as opposed to the conventional approach of using a sophisticated deep learner to make sentence-wide *** syllable level predictions help to lower the aggregated error in utterance level cross-corpus predictions. The experiments on IEMOCAP (IE), MSP-Improv (MI), and RAVDESS (RA) databases show that the method archives better than the state-of-the-art cross-corpus unweighted accuracy of 47.6% for IE to MI and 56.2% for MI to IE. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Large-Scale Hyperspectral Image Clustering Using Contrastive Learning

Large-Scale Hyperspectral Image Clustering Using Contrastive...

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2021 International Conference on Information and Knowledge Management Workshops, CIKMW 2021

作者： Cai, Yaoming Liu, Yan Zhang, Zijia Cai, Zhihua Liu, Xiaobo School of Computer Science China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China

Unsupervised hyperspectral image (HSI) classification is an important but challenging task in the hyperspectral processing community. Despite great success, previous HSI clustering approaches belong to offline clustering which is often performed in a transductive scheme, thus failing to generalize to large-scale and unseen scenes. In this paper, we propose an online and deep clustering model for large-scale HSI clustering, termed spectral-spatial contrastive clustering (SSCC). Specifically, SSCC performs contrastive learning based on a series of semantic-preserving spectral-spatial augmentation to simultaneously maximize the intra-class agreement and inter-class variation, which are implemented by an instance-level contrastive loss and a cluster-level contrastive loss, respectively. The SSCC model is trained in an end-to-end fashion with minibatch, allowing it to efficiently handle large-scale HSIs. We assess the performance of SSCC on real HSI and show that SSCC significantly advances the state-of-the-art results with 8.41% improvement on accuracy. © 2021 CEUR-WS. All rights reserved.

关键词： Spectroscopy

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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Chinese Journal of Electronics 2023年第3期19卷 451-456页

作者： Bo Li Wenju Liu Lihua Dou School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词： Training Image segmentation Analytical models Parameter estimation Estimation Probability density function Speech processing

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Human pose recognition based on multiple features and random forest algorithm 2

Human pose recognition based on multiple features and random...

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2nd International Conference on Computer Vision, Image, and Deep Learning

作者： Fang, Di Wang, Hong Meng, Fanglong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9781510646827

ISBN: (纸本)9781510646810

Human pose recognition based on bone node data collected by depth camera is a key problem in the field of human-computer interaction. To improve the accuracy of human pose recognition, a new algorithm based on multiple features and random forest model is proposed. Firstly, a 93-dimensional vector is defined, which contains the coordinate feature of the joint and the distance feature, and the distance feature is selected according to the spatial position of the joint. Then, in the process of body pose recognition, the random forest model is combined with Bagging algorithm to ensure the balance of samples, so as to improve the classification performance of the classifier for different samples. Finally, the performance test of the constructed classifier is carried out on the UTKinect-action3D Dataset. The experimental result shows that the algorithm can effectively identify a variety of human posture, and the recognition rate reaches more than 90%. The fusion of multiple features is of great significance to improve the accuracy of human posture recognition. © 2021 SPIE.

关键词： Decision trees

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A Novel Ceramic Surface Based Constant Force control Method for Flatness Inspection

SSRN

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SSRN 2023年

作者： Chen, Xin Gao, Xu Zhou, Yang Qin, Lang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

A constant force control method of the robot based on a force sensor is proposed for the difficult point of high difficulty and low accuracy of ceramic surface flatness inspection. This paper proposed a method that combines a constant impedance controller for normal contact force with a posture compliance controller. The method decomposes force control and position control orthogonally to simplify the complex three-dimensional surface model of ceramics. The method solves the problem that the end-effector is difficult to be perpendicular to the contact surface due to the change of ceramic surface shape. Moreover, the proposed method can also detect whether the ceramic surface is flat or not by the change of the force sensor's indication and the change of the actual end position of the robot arm. Finally, the defect detection experiments are conducted on a plane and on a complex surface, respectively. The experiments demonstrate the adaptability and fast convergence of the method proposed in this paper, which meets the needs of high precision and fast response of industrial processes. © 2023, The Authors. All rights reserved.

关键词： Force control

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Adaptive Sliding Mode control for Flexible Dual-manipulator with Friction Compensation

Adaptive Sliding Mode Control for Flexible Dual-manipulator ...

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Chinese automation Congress (CAC)

作者： Tao Song Shiqi Zheng Jiachun Sun Liangguang Li Qing Chang Zhipeng Li School of Automation China University of Geosciences Wuhan Campus Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex Systems Wuhan China

This paper focuses on the coordinated tracking control scheme of dual-manipulator based on friction compensation. First, a new dual-manipulator model with flexible joints and friction is constructed; Second, a new adaptive neural control method is proposed for the dual-manipulators with flexible joints. Neural networks are used to approximate the unknown nonlinear dynamics in the model; Third, new state observers are constructed to estimate the joint friction. Based on the observers, the friction can be well compensated. The stability of the system is derived by using Lyapunov method. The simulation results verify the effectiveness of the practical method.

关键词： Adaptation models Uncertainty Torque Friction Simulation Neural networks Observers

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Design and application of a one-stop mobile application sharing platform for steel enterprises

Design and application of a one-stop mobile application shar...

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第42届中国控制会议

作者： Xinzhe Chen Luefeng Chen Jie Hu Qingfeng Yang Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta

As china's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance.

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