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Ionization wave propagation and cathode sheath formation due to surface dielectric-barrier discharge sustained in pulsed mode

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plasma Science and technology 2023年第11期25卷 101-113页

作者： Konstantinos GIOTIS Panagiotis SVARNAS Eleftherios AMANATIDES Kristaq GAZELI Guillaume LOMBARDI Polykarpos K PAPADOPOULOS High Voltage Laboratory(Plasma Technology Room) Department of Electrical and Computer EngineeringUniversity of PatrasRion Patras 26504Greece Laboratoire des Sciences des Procédés et des Matériaux(LSPM—CNRS) UniversitéSorbonne Paris NordVilletaneuse F-93430France Plasma Technology Laboratory Department of Chemical EngineeringUniversity of PatrasRion Patras 26504Greece Department of Mechanical Engineering and Aeronautics University of PatrasRion Patras 26504Greece

This work deals with the experimental study of a surface dielectric-barrier discharge,as a part of the ongoing interest in the control of plasma induced electro-fluid dynamic effects(*** actuators).The discharge is generated using a plasma reactor consisting of a fused silica plate which is sandwiched between two printed circuit boards where the electrodes are *** reactor is driven by narrow high voltage square pulses of asymmetric rising(25 ns)and falling(2.5μs)parts,while the discharge evolution is considered in a temporarily and spatially resolved manner over these *** is,conventional electrical and optical emission analyzes are combined with high resolution optical emission spectroscopy and ns-resolved imaging,unveiling main characteristics of the discharge with a special focus on its propagation along the dielectric-barrier *** voltage rising part leads to cathode-directed ionization waves,which propagate with a speed up to 105m s~(-1).The voltage falling part leads to cathode sheath formation on the driven electrode.Τhe polarization of the dielectric barrier appears critical for the discharge dynamics.

关键词： atmospheric pressure plasma surface DBD streamer UV-NIR optical emission spectroscopy ICCD fast imaging(Some figures may appear in colour only in the online journal)

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Global practical stabilization of the double integrator system with an imperfect sensor and subject to a bounded disturbance

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Control Theory and technology 2024年第3期22卷 468-478页

作者： Zhiyuan Zhu Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai 200240China Charles L.Brown Department of Electrical and Computer Engineering University of VirginiaP.0.Box 400743CharlottesvilleVA 22904-4743USA

This paper is concerned with global practical stabilization of the double integrator system with an imperfect sensor and subject to an additive bounded output *** imperfect sensor nonlinearity possesses the nonlinear characteristics of saturation and dead *** of the presence of output dead zone and the additive disturbance,the states cannot be expected to driven into an arbitrarily small neighborhood of the *** solve the global practical stabilization problem,we proposes a low gain-based linear dynamic output feedback law,under which the first state enters and remains in a bounded set whose size is depended on the bound of disturbance and the range of dead zone and the second state enters and remains in a pre-specified arbitrarily small set,both in finite *** results illustrate the effectiveness of our proposed control method.

关键词： Output saturation Disturbance rejection Output dead zone Low gain feedback-Linear output feedback Practical stabilization

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Radiative cooling for passive thermal management towards sustainable carbon neutrality

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National Science Review 2023年第1期10卷 87-97页

作者： Jun Liang Jiawei Wu Jun Guo Huagen Li Xianjun Zhou Sheng Liang Cheng-Wei Qiu Guangming Tao Wuhan National Laboratory for Optoelectronics and Optics Valley Laboratory Huazhong University of Science and Technology Department of Electrical and Computer Engineering National University of Singapore MOE Key Laboratory of Thermo-Fluid Science and Engineering School of Energy and Power Engineering Xi'an Jiaotong University Key Laboratory of Education Ministry on Luminescence and Optical Information Technology National Physical Experiment Teaching Demonstration CenterDepartment of PhysicsSchool of Physical Science and Engineering Beijing Jiaotong University State Key Laboratory of Material Processing and Die &Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology

Photonic structures at the wavelength scale offer innovative energy solutions for a wide range of applications,from high-efficiency photovoltaics to passive cooling,thus reshaping the global energy *** cooling based on structural and material design presents new opportunities for sustainable carbon neutrality as a zero-energy,ecologically friendly cooling *** this review,in addition to introducing the fundamentals of the basic theory of radiative cooling technology,typical radiative cooling materials alongside their cooling effects over recent years are summarized and the current research status of radiative cooling materials is outlined and ***,technical challenges and potential advancements for radiative cooling are forecast with an outline of future application scenarios and development *** the future,radiative cooling is expected to make a significant contribution to global energy saving and emission reduction.

关键词： photonic structures radiative cooling energy saving and emission reduction carbon neutrality

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AI-driven material discovery for energy, catalysis and sustainability

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National Science Review 2025年第5期 77-78页

作者： Ning Han Bao-Lian Su Department of Electrical and Computer Engineering University of Toronto Laboratory of Inorganic Materials Chemistry(CMI) University of Namur State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology

Artificial intelligence (AI) is revolutionizing various sectors, including science,technology, industry and daily life [1,2].One key area where AI can make a significant impact is in material design, crucial for advan...

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Fire Security Systems Analysis and Internet of Things Implications

Fire Security Systems Analysis and Internet of Things Implic...

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2023 IEEE International Conference on Electro Information technology, eIT 2023

作者： Fuerte, Susana Rodriguez Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (纸本)9781665493765

This paper presents the current use of the Internet of Things (IoT) in fire evacuation and extinction. It examines the different approaches to the problem and technologies like Building Information Modeling (BIM) and mathematical algorithms that can be used to determine the optimal evacuation route. It also evaluates existing fire security solutions such as smoke, flame, motion, and gas sensors, LED lights, buzzers, and SMS modules. Entities that specialize in Residential and Commercial Security Systems and Home Automation are also discussed, along with the services they offer. The main objective of this study is to understand current systems and resources regarding fire evacuation and extinction systems and to analyze different developments in smart buildings to create an efficient system for fire detection and evacuation. © 2023 IEEE.

关键词： Internet of things

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Smart Infant Monitoring System Using computer Vision and AI

Smart Infant Monitoring System Using Computer Vision and AI

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2023 IEEE International Conference on Electro Information technology, eIT 2023

作者： Singh, Gurpreet Shekhar, Abhishek Raj Yu, Xinrui Saniie, Jafar Illinois Institute of Technology Embedded Computing and Signal Processing Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (纸本)9781665493765

The new era of technology is being greatly influenced by the field of artificial intelligence. computer vision and deep learning have become increasingly important due to their ability to process vast amounts of data and provide insights and solutions in a variety of fields. computer vision, deep learning and signal analysis have been used in a growing number of applications and services including smart devices, image, and speech recognition, healthcare, etc., one such device is an infant monitoring system. It monitors the daily activities of the infant such as their sleeping patterns, sounds, and movements. In this paper, deep learning and computer vision libraries were used to develop algorithms to detect whether the infant was in any uncomfortable situation such as sleeping on its back, face being covered and whether the infant was awake. The smart infant monitoring system detects the infant's unsafe resting situation in real time and sent immediate alerts to the caretaker's device. This paper presents the design flow of a smart infant monitoring system consisting of a night vision camera, a Jetson Nano, and a Wi-Fi internet connection. The pose estimation and awake detection algorithms were developed and tested successfully for different infant resting/sleeping situations. The smart infant monitoring system provides significant benefits for safety and an improved understanding of infants' sleep patterns and behavior. © 2023 IEEE.

关键词： Face recognition

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Multi-View Graph Embedding Learning for Image Co-Segmentation and Co-Localization

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IEEE Transactions on Circuits and Systems for Video technology 2024年第6期34卷 4942-4956页

作者： Huang, Aiping Li, Lijian Zhang, Le Niu, Yuzhen Zhao, Tiesong Lin, Chia-Wen Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou350108 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering The Fujian Science and Technology Innovation Laboratory for Optoelectronic Information Fuzhou350108 China Institute of Communications Engineering National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan

Image co-segmentation and co-localization exploit inter-image information to identify and extract foreground objects with a batch mode. However, they remain challenging when confronted with large object variations or complex backgrounds. This paper proposes a multi-view graph embedding (MV-Gem) learning scheme which integrates diversity, robustness and discernibility of object features to alleviate this phenomenon. To encourage the diversity, the deep co-information containing both low-layer general representations and high-layer semantic information is generated to form a multi-view feature pool for comprehensive co-object description. To enhance the robustness, a multi-view adaptive weighted learning is formulated to fuse the deep co-information for feature complementation. To ensure the discernibility, the graph embedding and sparse constraint are embedded into the fusion formulation for feature selection. The former aims to inherit important structures from multiple views, and the latter further selects important features to restrain irrelevant backgrounds. With these techniques, MV-Gem gradually recovers all co-objects through optimization iterations. Extensive experimental results on real-world datasets demonstrate that MV-Gem is capable of locating and delineating co-objects in an image group. © 1991-2012 IEEE.

关键词： Semantics

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Hyperautomation for Air Quality Evaluations: A Perspective of Evidential Three-way Decision-making

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Cognitive Computation 2024年第5期16卷 2437-2453页

作者： Ding, Juanjuan Zhang, Chao Li, Deyu Sangaiah, Arun Kumar School of Computer and Information Technology Shanxi University Shanxi Taiyuan030006 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Shanxi Taiyuan030006 China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Douliou64002 Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

Hyperautomation acts as a real digital transformation with the support of several cutting-edge cognitive computation methods that include robotic process automation, natural language processing, artificial intelligence, and other emerging ones, which is conducive to processing complex industrial processes via extending the range of various data-driven cognitive decision-making algorithms. The study of air quality evaluations (AQE) plays a significant role in ensuring healthy atmospheric environments. In view of the objective existence of uncertainties, AQE can be modeled and addressed by a typical data-driven automated decision-making problem, and hyperautomation can provide a reasonable solution via associating with a variety of techniques. This article explores hyperautomation for AQE via evidential three-way large-scale group decision-making (LSGDM) in an intuitionistic fuzzy (IF) setting. First, the notion of intuitionistic fuzzy sets (IFSs) is incorporated into the paradigm of multi-granularity (MG) three-way decisions (TWD), and the model of adjustable MG IF probabilistic rough sets (PRSs) is developed. Second, an IF clustering analysis with the improved technique for order preference by similarity to ideal solution (TOPSIS) method is conducted to affirm representative members within a decision group. Third, a novel IF LSGDM method is built via adjustable MG IF PRSs and the evidence reasoning (ER) method. Finally, a case study in the setting of AQE is studied by using the presented evidential three-way LSGDM method. Corresponding experimental analyses are carried out for illustrating the efficiency of hyperautomation for AQE. In general, the proposed method improves the performance of information fusion by virtue of adjustable MG IF PRSs, and the TOPSIS method avoids the influence of subjective factors on decision results. Meanwhile, the evaluation information of decision-makers (DMs) is fully analyzed by means of the ER method, which can provide more explaina

关键词： Decision making

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Segmentation of CAD models using hybrid representation

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虚拟现实与智能硬件(中英文) 2025年第2期7卷 188-202页

作者： Claude UWIMANA Shengdi ZHOU Limei YANG Zhuqing LI Norbelt MUTAGISHA Edouard NIYONGABO Bin ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Peace-Bay Academy of Virtual Reality Shenyang 110004China China Aerospace Systems Engineering Corporation Beijing 100070China Department of Signal and Information Processing Beihang UniversityBeijing 100191China Department of Computer Science University of SherbrookeSherbrooke J1C0A1Canada

In this paper,we introduce an innovative method for computer-aided design(CAD)segmentation by concatenating meshes and CAD *** previous CAD segmentation methods have achieved impressive performance using single representations,such as meshes,CAD,and point ***,existing methods cannot effectively combine different three-dimensional model types for the direct conversion,alignment,and integrity maintenance of geometric and topological ***,we propose an integration approach that combines the geometric accuracy of CAD data with the flexibility of mesh representations,as well as introduce a unique hybrid representation that combines CAD and mesh models to enhance segmentation *** combine these two model types,our hybrid system utilizes advanced-neural-network techniques to convert CAD models into mesh *** complex CAD models,model segmentation is crucial for model retrieval and *** partial retrieval,it aims to segment a complex CAD model into several simple *** first component of our hybrid system involves advanced mesh-labeling algorithms that harness the digitization of CAD properties to mesh *** second component integrates labelled face features for CAD segmentation by leveraging the abundant multisemantic information embedded in CAD *** combination of mesh and CAD not only refines the accuracy of boundary delineation but also provides a comprehensive understanding of the underlying object *** study uses the Fusion 360 Gallery *** results indicate that our hybrid method can segment these models with higher accuracy than other methods that use single representations.

关键词： B-RepNet hybrid segmentation CAD models classification MeshCNN MeshCAD-Net

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