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IEEE International Conference on Robotics and Automation (ICRA)

作者： Sehua Ji Weinan Chen Zerong Su Yisheng Guan Jiehao Li Hong Zhang Haifei Zhu Biomimetic and Intelligent Robotics Lab (BIRL) School of Electromechanical Engineer Guangdong University of Technology Guangzhou China JT-Innovation (Guangdong) Intelligent Technology Co. Ltd. Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing Guangdong Academy of Sciences Guangzhou China College of Engineering South China Agricultural University China Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Limited by the working principles, LiDAR-SLAM systems suffer from the degeneration phenomenon in environments such as long corridors and tunnels, due to the lack of sufficient geometric features for frame-to-frame matching. The accuracy and sensitivity of existing degeneracy detection methods need to be further improved. In this paper, we propose a novel method for degeneracy detection using local geometric models based on point-to-distribution matching. To obtain an accurate description of local geometric models, an adaptive adjustment of voxel segmentation according to the point cloud distribution and density is designed. The codes of the proposed method is open-source and available at https://***/jisehua/***. Experiments with public datasets and self-build robots were conducted to evaluate the methods. The results exhibit that our proposed method achieves higher accuracy than the other existing approaches. Applying our proposed method is beneficial for improving the robustness of the LiDAR-SLAM systems.

关键词： Point cloud compression Accuracy Simultaneous localization and mapping Sensitivity Laser radar Geometric modeling Noise

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Resistance potential of soil bacterial communities along a biodiversity gradient in forest ecosystems

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mLife 2022年第4期1卷 399-411页

作者： Jialiang Kuang Dongmei Deng Shun Han Colin T.Bates Daliang Ning Wensheng Shu Jizhong Zhou The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters Ministry of EducationSchool of Environment and EnergySouth China University of TechnologyGuangzhouChina Institute for Environmental Genomics and Department of Microbiology and Plant BiologyUniversity of OklahomaNormanOklahomaUSA State Key Laboratory of Biocontrol Guangdong Key Laboratory of Plant Resources and Conservation of Guangdong Higher Education InstitutesCollege of Ecology and EvolutionSun Yat-sen UniversityGuangzhouChina Guangxi Key Laboratory of Green Processing of Sugar Resources College of Biological and Chemical EngineeringGuangxi University of Science and TechnologyLiuzhouChina School of Life Sciences South China Normal UniversityGuangzhouChina School of Civil Engineering and Environmental Sciences University of OklahomaNormanOklahomaUSA School of Computer Sciences University of OklahomaNormanOklahomaUSA.8Earth and Environmental SciencesLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA.

Higher biodiversity is often assumed to be a more desirable scenario for maintaining the functioning of ecosystems,but whether species-richer communities are also more disturbance-tolerant remains *** this study,we investigated the bacterial communities based on 472 soil samples from 28 forests across China with associated edaphic and climatic *** developed two indexes(i.e.,community mean tolerance breadth[CMTB]and community mean response asynchrony[CMRA])to explore the relationship between diversity and community resistance ***,we examined this resistance potential along the climatic and latitudinal *** revealed that CMTB was significantly and negatively related to species richness,resulting from the changes in balance between relative abundances of putative specialists and *** comparison,we found a unimodal relationship between CMRA and richness,suggesting that higher biodiversity might not always lead to higher community ***,our results showed differential local patterns along *** particular,local patterns in the northern region mainly followed general relationships rather than those for the southern forests,which may be attributed to the differences in annual means and annual variations of climate *** findings highlight that the community resistance potential depends on the composition of diverse species with differential environmental tolerance and *** study provides a new,testable evaluation by considering tolerance breadth and response asynchrony at the community level,which will be helpful in assessing the influence of disturbance under rapid shifts in biodiversity and species composition as a result of global environmental change.

关键词： ecological resistance forest soil bacterial community latitudinal gradient specialist–generalist balance species richness

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Benefits and drawbacks of radiofrequency ablation via percutaneous or minimally invasive surgery for treating hepatocellular carcinoma

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World Journal of Gastrointestinal Surgery 2024年第11期16卷 3400-3407页

作者： Ching-Lung Hsieh Cheng-Ming Peng Chun-Wen Chen Chang-Hsien Liu Chih-Tao Teng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724Taiwan Department of Surgery Chung Shan Medical University HospitalTaichung 40201Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Department of Radiology Taichung Armed Forces General HospitalTaichung 406Taiwan Department of Medical Imaging and Radiological Sciences Central Taiwan University of Science and TechnologyTaichung 406Taiwan Department of Radiology School of MedicineNational Defense Medical CenterTaipei 11490Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital and China Medical UniversityHsinchu 302Taiwan Institute of Nuclear Engineering and Science National Tsing Hua UniversityHsinchu 300Taiwan Department of Radiology Nantou Hospital of the Ministry of Health and WelfareNantou 540Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia UniversityTaichung 407Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

The management of early stage hepatocellular carcinoma(HCC)presents significant *** radiofrequency ablation(RFA)has shown safety and effectiveness in treating HCC,with lower mortality rates and shorter hospital stays,its high recurrence rate remains a significant ***,achieving improved survival solely through RFA is challenging,particularly in retrospective studies with inherent *** is commonly used for guiding percutaneous RFA,but its low contrast can lead to missed tumors and the risk of HCC *** enhance the efficiency of ultrasound-guided percutaneous RFA,various techniques such as artificial ascites and contrast-enhanced ultrasound have been developed to facilitate complete tumor *** invasive surgery(MIS)offers advantages over open surgery and has gained traction in various surgical *** studies suggest that laparoscopic intraoperative RFA(IORFA)may be more effective than percutaneous RFA in terms of survival for HCC patients unsuitable for surgery,highlighting its ***,combining MIS-IORFA with these enhanced percutaneous RFA techniques may hold greater significance for HCC treatment using the MIS-IORFA *** article reviews liver resection and RFA in HCC treatment,comparing their merits and proposing a trajectory involving their combination in future therapy.

关键词： Percutaneous radiofrequency ablation Minimally invasive surgery Hepatocellular carcinoma Intraoperative radiofrequency ablation Contrast-enhanced ultrasound

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WiWm-EP: Wi-Fi CSI-based Wheat Moisture Detection Using Equivalent Permittivity

WiWm-EP: Wi-Fi CSI-based Wheat Moisture Detection Using Equi...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Pengming Hu Weidong Yang Xuyu Wang Shiwen Mao Erbo Shen Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Zhengzhou College of Information Science and Engineering Henan University of Technology Zhengzhou China Knight Foundation School of Computing and Information Sciences Florida International University FL USA Department of Electrical and Computer Engineering Auburn University Auburn AL

Moisture content is one of the important indexes of food storage security. The existing detection methods are time-consuming and high cost such that it is difficult to realize online moisture detection. In this paper, according to the dielectric properties of wheat, we propose a wheat moisture content detection system with commercial Wi-Fi devices, termed WiWm-EP. First, we introduce the relationship between the moisture content of wheat and its dielectric constant. Then, we establish an equivalent permittivity (EP) model to characterize wheat moisture content, where the EP can be calculated from channel state information (CSI) of the dual antenna model. Besides, we build the fitting function between the EP and the moisture content as the wheat moisture detection model. Finally, we evaluate the performance of the system through different experiments. The average relative error of the detection results of five wheat samples with different moisture contents is less than 3%.

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Navigating the future:Embracing resilience and interoperability in the industrial internet

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Fundamental Research 2024年第1期4卷 1-2页

作者： Chaojie Gu Chunxiao Jiang Jiming Chen Yang Cong Bin Xiao College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Division II Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Chongqing Key Laboratory of Image Cognition School of Computer Science and TechnologyChongqing University of Posts and TelecommunicationsChongqing 400065China

In the midst of the fourth industrial revolution,the convergence of the digital,physical,and biological realms is propelling industrial innovation to new *** the heart of this transformative era lies the Industrial In... 详细信息

关键词： internet network shaping

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Optimization of DCM boost chopper performance controlled by optimal PIDF regulator for stand-alone PV system

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Solar Compass 2025年 14卷

作者： Nkouna Paul Lionnel, Ella Obono Biyobo, Arnaud Owoundi Etouke, Paul Dangwe Sounsoumou, Yves Paulin Jean Jacques Molu, Reagan Dzonde Naoussi, Serge Raoul Computer and Automatic Engineering Research Laboratory ENSET University of Douala Douala Cameroun PB: 1872 Douala Cameroon Faculty of Science Renewable Energies Department University of Garoua Garoua Cameroon PB 346 Garoua Cameroon Technologies and Applied Sciences Laboratory University Institute of Technology of Douala University of Douala P.O. Box: 8689 Douala Cameroon

This paper proposes a Maximum Power Point Tracking (MPPT) strategy for a photovoltaic (PV) panel, combining the Perturb and Observe (P&O) technique, Particle Swarm Optimization (PSO), and an optimal Duty Cycle Modulation (DCM) circuit. The Boost chopper, regulated by a Proportional-Integral-Derivative controller with a first-order low-pass filter (PIDF), serves as an interface between the photovoltaic source (PV) and the load, maximizing the extraction of energy produced by the solar panel. The results obtained in virtual simulation in the MATLAB/Simulink environment are satisfactory: we observe in standard conditions, namely temperature T = 25 °C and solar irradiation of 1000W/m², a response without overshoot, a zero static error, a system stability time of 0.32 s, 0.13 s and 0.15 s respectively for three respective load values (R₀ = 50 Ω, R₀₁ = 37.5 Ω and R₀₂ = 25 Ω) in steady state. In transient state, taking into account the variation in solar irradiation, it can be seen that despite the fluctuations, the system manages to remain stable, attesting to the robustness of the controller used. To control the DCM Boost chopper. The comparative study carried out with other MPPT techniques such as (VSS-P&O, MIC, FOCV, FSS-RBFA, VSS-RBFA, AFLC, PSO and CS) applied to conventional boost converters attests that the proposed new prototype offers quite satisfactory performances compared to the latter. © 2025 The Author(s)

关键词： DCM (duty cycle modulation) LQR (linear quadratic regulator) P&O (Perturb and Observe) PIDF (Proportional, Integral, Derivative with low-pass Filter) PSO (Particle Swarm Optimization)

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Integration of ANN for Accurate Estimation and control in Wastewater Treatment

Integration of ANN for Accurate Estimation and Control in Wa...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Andreea Elena Țîru Iulian Vasiliev Larisa Diaconu Ramon Vilanova Daniel Voipan Harsha Ratnaweera Department of Automatic Control and Electrical Engineering "Dunărea de Jos" University of Galaţi Galaţi Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain Department of Computer Science and Information Technology "Dunărea de Jos" University of Galaţi Galaţi Romania Faculty of Science and Technology (Realtek) Norwegian University of Life Sciences Ås Norway

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so.

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Reset controller Synthesis by Reach-avoid Analysis for Delay Hybrid Systems

arXiv

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arXiv 2023年

作者： Su, Han Zhu, Jiyu Feng, Shenghua Bai, Yunjun Gu, Bin Liu, Jiang Yang, Mengfei Zhan, Naijun Institute of Software University of Chinese Academy of Sciences Beijing China Zhongguancun Laboratory Beijing China Beijing Institute of Control Engineering Beijing China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China China Academy of Space Technology Beijing China School of Computer Science Peking University Beijing China

A reset controller is pivotal in the design of hybrid systems. It restricts the initial set and redefines the reset map associated with discrete transitions, ensuring system objective is met. Reset controller synthesis, alongside feedback controller synthesis and switching logic controller synthesis, provides a correct-by-construction approach to designing hybrid systems. However, the presence of time-delay poses challenges in hybrid systems, potentially compromising control performance and rendering verification certificates obtained by abstracting away time-delay invalid in practice. This paper addresses this issue by proposing a approach that incorporates time-delay considerations. We introduce a method that reduces the synthesis of reset controllers to the generation of reach-avoid sets for the hybrid system at hand, which can be efficiently solved using standard convex optimization solvers. © 2023, CC BY-NC-ND.

关键词： controllers

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Exploiting the Intrinsic Neighborhood Semantic Structure for Domain Adaptation in EEG-based Emotion Recognition

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IEEE Transactions on Affective Computing 2025年

作者： Yang, Yi Wang, Ze Song, Yu Jia, Ziyu Wang, Boyu Jung, Tzyy-Ping Wan, Feng Macau University of Science and Technology Macao Centre for Mathematical Sciences Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovation Engineering 999078 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin300384 China Chinese Academy of Sciences Beijing Key Laboratory of Brainnetome and Brain-Computer Interface and Brainnetome Center Institute of Automation Beijing100045 China Western University Department of Computer Science Brain Mind Institute LondonONN6A 3K7 Canada University of California at San Diego Swartz Center for Computational Neuroscience Institute for Neural Computation La Jolla CA92093 United States University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China University of Macau Centre for Cognitive and Brain Sciences Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation 999078 China

Due to the inherent non-stationarity and individual differences present in electroencephalogram (EEG) signals, developing a generalizable model that performs well on new subjects is challenging in EEG-based emotion recognition. Most existing domain adaptation (DA) methods typically mitigate these discrepancies by aligning the marginal distributions of domain feature representations. However, when there is a significant difference in the class-conditional distribution between domain features and labels, the domain-invariant features learned by aligning marginal distributions may have limited discriminative ability for unlabeled target instances or even prove counterproductive. To address this issue, we propose a Neighborhood Semantic Aware Learning-based Dynamic Graph Attention Convolution (NSAL-DGAT) approach that learns target semantic information by considering the inter-domain semantic topological structure, thereby improving classifier adaptation for target instances. Specifically, the proposed NSAL framework is designed to capitalize on the insight that after domain feature alignment, some target samples and their neighboring source samples exhibit similar semantics. By leveraging the neighborhood topological structure, we extract and incorporate semantic target features to train a more transferable classifier. Besides, we implement an entropy weighting mechanism to emphasize representative target semantic information, encouraging target instances to prioritize high-confidence individuals within the source neighborhood. We have conducted extensive experiments on the public SEED dataset and our collected the Hearing-Impaired EEG Dataset (HIED). The experimental results underscore the efficacy of our proposed NSAL-DGAT approach, showcasing state-of-the-art accuracy in subject-dependent as well as subject-independent scenarios. The source code is available at https://***/YYingDL/NSAL-DGAT. © 2010-2012 IEEE.

关键词： Speech analysis

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Adaptive ELM-Based Time-Constrained control of Uncertain Robotic Manipulators With Minimum Learning Computation

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IEEE Transactions on Emerging Topics in Computing 2025年

作者： Jin, Xiaozheng Hou, Yuhan Wu, Xiaoming Chi, Jing Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Shandong Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Jinan250013 China Qilu Institute of Technology School of Intelligent Manufacturing and Control Engineering Shandong Jinan250200 China Shandong University of Finance and Economics School of Computing and Artificial Intelligence Shandong Jinan250014 China

This paper studies the extreme learning machine (ELM)-based time-constrained trajectory tracking control of a class of robotic manipulator systems with model/input uncertainties, matched and mismatched disturbances. A uniform robust exact differentiator (URED) is developed to construct a multi-layer virtual control framework of the robotic manipulator system. Under the control framework, adaptive ELM-based control strategies are proposed to suppress the influence of the uncertainties and disturbances layer-by-layer, combining with the minimum learning parameter (MLP) technique which is employed to reduce the calculation complexity of ELM parameters. The significance of this study is that general model/input uncertainties, matched and mismatched disturbances can be effectively compensated within a limited time, so that bounded trajectory tracking of the robotic manipulator can be achieved avoiding the complexity explosion issue. The time-constrained stability of the closed-loop robotic error systems is proved through Lyapunov stability theory. Finally, comparative simulations are employed to display the feasibility and superiority of the designed robust adaptive ELM-based control schemes of a robotic manipulator system. © 2013 IEEE.

关键词： Robust control

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