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第40届中国控制会议

作者： Min Li Luefeng Chen Min Wu Witold Pedrycz Kaoru Hirota 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 Tokyo Institute of Technology

Multimodal information-based broad and deep learning model（MIBDL） for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using different processing methods of deep network and broad network, which obtains the features of depth and width dimensions. Moreover, random mapping in the initial broad learning network could cause information loss and its shallow layer network is difficult to cope with complex tasks. To address this problem, we use principal component analysis to generate the nodes of the broad learning, and the stacked broad learning network is adapted to make it easier for the existing broad learning networks to cope with complex tasks by creating deep variations of the existing network. To verify the effectiveness of the proposal, experiments completed on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-theart methods. According to the simulation experiments on the FABO database, by using the proposed method, the multimodal recognition rate is 17,54%, 1.24%, and 0.23% higher than those of the temporal normalized motion and appearance features（TN）,the multi-channel CNN（MCCNN）, and the hierarchical classification fusion strategy（HCFS）, respectively.

关键词： Convolution neural network broad learning emotion understanding facial expression body gesture

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On-The-Fly CNC interpolation using frequency-domain FFT-based filtering

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Procedia CIRP 2022年 107卷 1571-1576页

作者： Rob Ward Burak Sencer George Panoutsos Erdem Ozturk Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK Advanced Manufacturing Research Centre University of Sheffield Rotherham S60 5TZ UK Mechanical Engineering Department Oregon State University Corvallis OR USA

Finite Impulse Response filtering is increasingly becoming the interpolation method of choice in modern computer numerically controlled (CNC) machining centres. Recently, On-The-Fly (OTF) interpolation was introduced using direct convolution to adaptively change the FIR flter time constant throughout the toolpath. In this paper, it is shown that computational advantages can be gained by using frequency domain methods instead. This paper introduces a novel on-the-fly CNC interpolation method using Fast Fourier Transforms (FFTs). The presented OTF FFT method demonstrates up to 10 times increase in computational speed than the direct convolution OTF method. The effectiveness of the proposed method is validated in simulation based case studies.

关键词： CNC Interpolation FFT Convolution Motion control

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A novel signal processing algorithm for measurement while drilling(MWD) system

A novel signal processing algorithm for measurement while dr...

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第40届中国控制会议

作者： ShiLong Cheng Yule Hu 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 Faculty of Engineering China University of Geosciences

Measurement while drilling(MWD) is a widely used signal transmission technology in the drilling *** present,the domestic pulse identification method is relatively simple,using the basic threshold method to identify,only set the threshold which will leading a number of missing detection mud pulse in the complex working *** this paper,a novel data processing algorithm is proposed for measurement while drilling *** method designed in this paper identifies the start time of data frame by using correlation coefficient and synchronization head model,then,based on the principle that the amplitude of mud pulse signal is larger than that of noise pulse signal,the maximum pulse signal in the length of a group of mud pulse series is extracted as mud pulse *** simulation is executed using the data from the actual drilling process and the results show the effectiveness of the proposed method.

关键词： Measurement while drilling Pulse recognition Correlation coefficient Sliding time window

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Pseudo-LiDAR for Visual Odometry

arXiv

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arXiv 2022年

作者： Deng, Huiying Wang, Guangming Feng, Zhiheng Jiang, Chaokang Wu, Xinrui Miao, Yanzi Wang, Hesheng Advanced Robotics Research Center AI Research Institute School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

As one of the important tasks in the field of robotics and machine vision, LiDAR/visual odometry provides tremendous help for various applications such as navigation, location, etc. In the existing methods, LiDAR odometry shows superior performance, but visual odometry is still widely used for its price advantage. Conventionally, the task of visual odometry mainly rely on the input of continuous images. However, it is very complicated for the odometry network to learn the epipolar geometry information provided by the images. In this paper, the concept of pseudo-LiDAR is introduced into the odometry to solve this problem. The pseudo-LiDAR point cloud back-projects the depth map generated by the image into the 3D point cloud, which changes the way of image representation. Compared with the stereo images, the pseudo-LiDAR point cloud generated by the stereo matching network can get the explicit 3D coordinates. Since the 6 Degrees of Freedom (DoF) pose transformation occurs in 3D space, the 3D structure information provided by the pseudo-LiDAR point cloud is more direct than the image. Compared with sparse LiDAR, the pseudo-LiDAR has a denser point cloud. In order to make full use of the rich point cloud information provided by the pseudo-LiDAR, a projection-aware dense odometry pipeline is adopted. Most previous LiDAR-based algorithms sampled 8192 points from the point cloud as input to the odometry network. The projection-aware dense odometry pipeline takes all the pseudo-LiDAR point clouds generated from the images except for the error points as the input to the network. While making full use of the 3D geometric information in the images, the semantic information in the images is also used in the odometry task. The fusion of 2D-3D is achieved in an image-only based odometry. Experiments on the KITTI dataset prove the effectiveness of our method. To the best of our knowledge, this is the first visual odometry method using pseudo-LiDAR. Copyright © 2022, The Authors. A

关键词： Pipelines

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Motion Transfer based on Front and Back View for Rehabilitative Exercise

Motion Transfer based on Front and Back View for Rehabilitat...

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第40届中国控制会议

作者： Yuting Ge Jinhua She Chi Xu 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 School of Engineering Tokyo University of Technology

As a part of rehabilitation training,rehabilitation gymnastics plays an important role in restoring the patients’ bodily *** facilitate the evaluation of rehabilitation exercises,in this work we propose multi-view on a motion transfer framework which is based on GANs and parameterized human *** we can generate virtual exercise images sampled from the front and back view of one person with the appearance *** transfer methods based on 2D information can hardly deal with the ambiguity of human pose and lack of appearance ***,this work uses a 3D parametric human model to represent the human body and poses,sampling,and combining pixels from pictures token from both front and back view of a source character,to generate target images under given *** whole framework we used can be divided into three stages.1) In the first stage the 3D human mesh will be reconstructed.2) In the second stage,transformation maps of multi-view will be calculated,which can show the coordinates of required pixels for sampling and placing.3) In the third stage,a generated adversarial network is employed to optimize the coarse result from the second stage and make it more *** our experiments,the whole framework achieves good results,especially it is proved that sampling features from both the front and back view can preserve more details of appearance by comparison experiment.

关键词： Motion transfer Rehabilitation exercises Deep learning Generative Adversarial Network

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Ending Weight Stigma to Advance Health Equity

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American Journal of Preventive Medicine 2024年第5期67卷 785-791页

作者： Pearl, Rebecca L. Donze, Laurie Friedman Rosas, Lisa G. Agurs-Collins, Tanya Baskin, Monica L. Breland, Jessica Y. Byker Shanks, Carmen Cooksey Stowers, Kristen Johnson, Shaneeta Lee, Bruce Y. Martin, Michelle Y. Mujuru, Priscah Odoms-Young, Angela Panza, Emily Pronk, Nicolaas P. Calicutt, Kesha Nadglowski, Joe Nece, Patricia M. Tedder, Michele Chow, Lisa S. Krishnamurti, Harini Jay, Melanie Xi, Dan Jastreboff, Ania M. Stanford, Fatima Cody Department of Clinical and Health Psychology University of Florida National Heart Lung and Blood Institute National Institutes of Health Department of Epidemiology and Population Health and Department of Medicine Stanford University Division of Cancer Control and Population Sciences National Cancer Institute Department of Medicine University of Pittsburgh School of Medicine Center for Innovation to Implementation VA Palo Alto Health Care System Center for Nutrition & Health Impact Department of Allied Health Science and Rudd Center for Food Policy and Health University of Connecticut Department of Surgery and Satcher Health Leadership Institute Morehouse School of Medicine Public Health Computational and Operation Research (PHICOR) Artificial Intelligence Modeling and Informatics for Nutrition Guidance and Systems (AIMINGS) CATCH (Center for Advanced Technology and Communication in Health) City University of New York (CUNY) Graduate School of Public Health and Health Policy Center for Innovation in Health Equity Research Department of Preventive Medicine College of Medicine University of Tennessee Health Science Center National Institute on Minority Health and Health Disparities Division of Nutritional Sciences College of Human Ecology Cornell University Department of Psychiatry and Human Behavior Warren Alpert Medical School of Brown University and Weight Control and Diabetes Research Center The Miriam Hospital HealthPartners Institute Obesity Action Coalition Black Women's Health Imperative Department of Medicine Division of Diabetes Endocrinology and Metabolism University of Minnesota Department of Psychological and Brain Sciences The George Washington University NYU Grossman School of Medicine Departments of Medicine and Population Health and Veterans Affairs Division of Cancer Treatment and Diagnosis National Cancer Institute Department of Medicine (Endocrinology) and Pediatrics (Endocrinology) Yale School of Medicine Massachusetts General Hospital MGH Weight Center Departmen

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Stabilization of discrete time stochastic linear systems with time delay via event-triggered control

Stabilization of discrete time stochastic linear systems wit...

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Chinese automation Congress (CAC)

作者： Jian Dong Xiaofeng Zong 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 Wuhan People’s Republic of China

ISBN: (纸本)9781665426480

This paper presents the stabilization problem of a class of discrete-time stochastic linear systems with time delay using an event-triggered control(ETC) strategy. For the general linear systems, we propose a new event triggering mechanism and deduce sufficient conditions for mean square exponentially stabilizability(MSES) and almost sure exponentially stabilizability(ASES) via ETC. The results show that the stability of the system depends on the system parameters (time delay, noise, event trigger threshold parameter, and unstable characteristic value of the original system). When the feedback control is disturbed by low-intensity noise, the unstable system can be stable in the mean square. Finally, the validity of the theoretical results is illustrated through a simulation example.

关键词： Linear systems Sufficient conditions automation Delay effects Stability analysis Feedback control

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Graphene-nickel nitride hybrids supporting palladium nanoparticles for enhanced ethanol electrooxidation

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Journal of Energy Chemistry 2021年第4期30卷 48-54页

作者： Tong Wu Xiao Wang Ahmet Emrehan Emre Jinchen Fan Yulin Min Qunjie Xu Shigang Sun Shanghai Key Laboratory of Materials Protection and Advanced Materials in Electric Power Shanghai Engineering Research Center of Energy-Saving in Heat Exchange SystemsShanghai University of Electric PowerShanghai 200090China Department of Chemical Engineering and Biointerfaces Institute University of MichiganAnn Arbor 48109MIUnited States Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China State Key Laboratory of Physical Chemistry of Solid Surfaces Department of ChemistryCollege of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005FujianChina

Electrocatalysts for ethanol oxidation reaction(EOR)are generally limited by their poor durability because of the catalyst poisoning induced by the reaction intermediate carbon monoxide(CO).Therefore,the rapid oxidation removal of CO intermediates is crucial to the durability of EOR-based ***,in order to effectively avoiding the catalyst CO poisoning and improve the durability,the graphene-nickel nitride hybrids(AG-Ni_(3)N)were designed for supporting palladium nanoparticles(Pd/AG-Ni_(3)N)and then used for ethanol *** density functional theory(DFT)calculations demonstrated the introduction of AG-Ni_(3)N depresses the CO absorption and simultaneously promotes the adsorption of OH species for CO oxidation *** fabricated Pd/AG-Ni_(3)N catalyst distinctively exhibits excellent electroactivity with the mass catalytic activity of 3499.5 m A mg^(-1) on EOR in alkaline media,which is around 5.24 times higher than Pd/C(commercial catalyst).Notably,the Pd/AG-Ni_(3)N hybrids display excellent stability and durability after chronoamperometric measurements with a total operation time of 150,000 s.

关键词： Graphene Pd nanoparticles Nickel nitride Ethanol electrooxidation

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Smart Infrared Temperature Measurement System Based On Elastic Compute Service Platform

Smart Infrared Temperature Measurement System Based On Elast...

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Chinese automation Congress (CAC)

作者： Yongbo Li Li Yuan 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 Wuhan People’s Republic of China

ISBN: (纸本)9781665426480

In the fight against the novel coronavirus, this paper designs a smart infrared temperature measurement system based on the Elastic Compute Service platform. In the perceptual layer part of the Internet of Things(IoT), the system uses infrared temperature sensors to quickly collect the temperature of the forehead or arm of the human body and Uses the MCU to automatically transmits the measured data to the Elastic Compute Service through the WiFi module. In the network layer part of the Internet of Things,the data written into the database of the Elastic Compute Service through the program deployed on the Elastic Compute Service. In the application layer of the Internet of Things, the remote management terminal monitors the collected body temperature data in real-time and provides quick warnings. Finally, the User can log in to the applet on his mobile phone to quickly and easily obtain personal information.

关键词： Temperature measurement Temperature sensors Temperature distribution Forehead Databases Real-time systems Mobile handsets

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Nearest-Better Network for Fitness Landscape Analysis of Continuous Optimization Problems

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IEEE Transactions on Evolutionary Computation 2024年

作者： Diao, Yiya Li, Changhe Zeng, Sanyou Yang, Shengxiang Coello, Carlos A. Coello China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Anhui University of Sciences and Technology School of Artificial Intelligence Hefei China China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan China De Montfort University School of Computer Science and Informatics LeicesterLE1 9BH United Kingdom Department of Computer Science CINVESTAV-IPN 07360 Mexico Tecnologico de Monterrey Faculty of Excellence The School of Engineering and Sciences N.L. Monterrey Mexico

Fitness landscape analysis (FLA) is quite important in evolutionary computation. In this paper, we propose a novel FLA method, the nearest-better network (NBN), which uses the nearest-better relationship to simplify the original fitness landscape of continuous optimization problems. We introduce an efficient algorithm to calculate NBN for continuous problems. We also propose four numerical measurements and a 3D visualization method based on NBN. Experiments show that compared to the other main FLA methods, the four numerical measurements proposed here can effectively measure the four intended features: neutrality, ruggedness, modality, and basin of attraction, respectively, and common features of the fitness landscape can be maintained in 3D NBN visualization, regardless of the scale of the problem. NBN also provides a view of how algorithms search in high-dimensional problems with the help of the 3D NBN visualization. © 1997-2012 IEEE.

关键词： Optimization algorithms

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