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IEEE International Conference on Industrial technology (ICIT)

作者： Fan Yang Yuening Huang Chao Zhai Hehong Zhang China University of Geosciences Wuhan Campus School of Automation 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 China Rice University George R. Brown School of Engineering and Computing Houston Texas United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints.

关键词： Autism Filters Reinforcement learning Games Variable speed drives Motors Trajectory Safety Mirrors Motion control

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Konjac glucomannan (KGM) aerogel immobilized microalgae: A new way for marine oil spills remediation

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Marine Pollution Bulletin 2025年 218卷 118158页

作者： Wang, Xudong Du, Zhuorong Song, Zhao Liu, Mei He, Pengfei Feng, Lijuan Chen, Zhi Chen, Qingguo Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry Zhejiang Ocean University Zhoushan316022 China National & local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology Zhejiang Ocean University Zhoushan316022 China School of Marine Science & Technology Zhejiang Ocean University Zhoushan316022 China Zhejiang Marine Fisheries Research Institute Zhoushan316021 China Department of Building Civil and Environmental Engineering Faculty of Engineering & Computer Sciences Concordia University MontrealQCH3G1M8 Canada

This study investigated the oil pollution remediation ability of konjac glucomannan (KGM) aerogel immobilized Chlorella vulgaris LH-1 (C. vulgaris). The KGM aerogel exhibited a high porosity of 86.83 %, and with the change of crude oil concentration (1–10 g/L), the crude oil adsorption efficiency of KGM aerogel was up to 18.75 %. The KGM aerogel carrier enhanced the crude oil biodegradation efficiency of C. vulgaris by 13.86 %. The concentration of residual n-alkanes of the immobilized C. vulgaris group was only 36.83 % of that of the free C. vulgaris group after 14 days of cultivation. In the crude oil metabolites of immobilized C. vulgaris, the concentrations of benzoic acid, phthalic acid, and benzophenone were 1.35, 21.18 and 3.43 times higher than those of the free C. vulgaris, respectively. Compared with free C. vulgaris group, 9 monooxygenase genes, 11 dioxygenase genes and 2 cytochrome P450 genes of immobilized C. vulgaris group were up-regulation and the "hydrocarbon metabolism process" was significantly enriched (enrichment factor is 0.85) in the gene ontology (GO) analysis of the transcriptome of C. vulgaris. These results showed that the ability of C. vulgaris to degrade crude oil was improved due to the existence of the KGM aerogel immobilized carrier. © 2025 Elsevier Ltd

关键词： Marine pollution

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Erratum to: Optimized design of a reinforced exhaust at low velocity (RELV) system for efficient viral aerosol removal in elevators (Building Simulation, (2025), 10.1007/s12273-025-1258-2)

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Building Simulation 2025年 1-1页

作者： Liu, Sumei Xu, Longhui Chen, Bingqian Deng, Zhipeng Du, Chengbo Li, Pin Zhao, Runmin Tianjin Key Laboratory of Indoor Air Environmental Quality Control School of Environmental Science and Engineering Tianjin University Tianjin300072 China School of Energy and Electrical Engineering Qinghai University Xining810016 China BYD Auto Industry Company Limited Shenzhen518119 China Department of Mechanical and Aerospace Engineering College of Engineering and Computer Science University of Central Florida OrlandoFL32816 United States School of Mechanical Engineering Purdue University West LafayetteIN47907 United States Shanghai Junyu Information Technology Co. Ltd Shanghai China

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Adaptive Decentralized Output-Constrained control of Single-Bus DC Microgrids

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IEEE/CAA Journal of automatica Sinica 2019年第2期6卷 424-432页

作者： Jiangkai Peng Bo Fan Jiajun Duan Qinmin Yang Wenxin Liu the Smart Microgrid and Renewable Technology (SMRT) Research Laboratory Department of Electrical and Computer Engineering Lehigh University the State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University the GEIRI North America

A single-bus DC microgrid can represent a wide range of applications. control objectives of such systems include high-performance bus voltage regulation and proper load sharing among multiple distributed generators(DGs) under various operating conditions. This paper presents a novel decentralized control algorithm that can guarantee both the transient voltage control performance and realize the predefined load sharing percentages. First, the output-constrained control problem is transformed into an equivalent unconstrained one. Second, a two-step backstepping control algorithm is designed based on the transformed model for bus-voltage regulation. Since the overall control effort can be split proportionally and calculated with locally-measurable signals, decentralized load sharing can be realized. The control design requires neither accurate parameters of the output filters nor load measurement. The stability of the transformed systems under the proposed control algorithm can indirectly guarantee the transient bus voltage performance of the original system. Additionally, the high-performance control design is robust, flexible, and reliable. Switch-level simulations under both normal and fault operating conditions demonstrate the effectiveness of the proposed algorithm.

关键词： DC microgrids decentralized control paralleled converters output constraint

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Deep reinforcement learning and its application in autonomous fitting optimization for attack areas of UCAVs

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Journal of Systems engineering and Electronics 2020年第4期31卷 734-742页

作者： LI Yue QIU Xiaohui LIU Xiaodong XIA Qunli School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Science and Technology on Electro-Optic Control Laboratory Luoyang 471000China Beijing Aerospace Automatic Control Research Institute Beijing 100854China

The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.

关键词： attack area neural network deep deterministic policy gradient(DDPG) unmanned combat aerial vehicle(UCAV)

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Internal short circuit fault diagnosis for automotive lithium-ion batteries using an adaptive parameter identification model

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Measurement: Journal of the International Measurement Confederation 2025年 253卷

作者： Tao, Qian Wang, Yiming Tian, Engang Tao, Hongfeng Chen, Hongtian Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi Jiangsu214122 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

This paper develops a model-based diagnostic method for internal short circuit (ISC) faults in lithium-ion batteries. This method utilizes a second-order equivalent circuit model (ECM) combined with a recursive least squares method with an adaptive forgetting factor for online parameter identification, with initial parameters optimized by a particle swarm optimization (PSO) algorithm. An extended Kalman filter (EKF) is then employed for state estimation to generate residuals, which are analyzed using the refined cumulative sum (CUSUM) statistical method to detect and diagnose ISC faults. Experimental results show that this method effectively identifies ISC faults in automotive power batteries under various initial state of charge (SOC) levels and fault-free conditions. At 100% initial SOC, fault detection times are 104 seconds for a 15Ω fault, 77 seconds for a 10Ω fault, and 27 seconds for a 1Ω fault;at 90% initial SOC, detection for a 10Ω fault takes 97 seconds, demonstrating high accuracy and robustness. © 2025 Elsevier Ltd

关键词： Lithium-ion batteries

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Tissue P Systems with Look-ahead Mode

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Chinese Journal of Electronics 2014年第1期23卷 81-86页

作者： JIANG Yun SONG Tao ZHANG Zheng School of Computer Science and Information Engineering Chongqing Technology and Business University Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology

Tissue P systems are a class of distributed and parallel computing models inspired from inter-cellular communication and cooperation between cells. In this work, a variant of tissue P system, named tissue P system with look-ahead mode, is discussed for decreasing the inherent non-determinism of tissue P systems and helping implementing tissue P systems on computers. Such systems are proved to be universal by simulating register machine, and they are also proved to be able to efficiently solve computationally hard problems by means of a spacetime tradeoff, which is illustrated with a polynomial solution to 3-coloring problem.

关键词： Tissue P system Look-ahead mode Recursively enumerable language Cell separation 3-Coloring

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Altering the Residual Stress in High-Carbon Steel through Promoted Dislocation Movement and Accelerated Carbon Diffusion by Pulsed Electric Current

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Acta Metallurgica Sinica(English Letters) 2023年第9期36卷 1511-1522页

作者： Kun Yi Siqi Xiang Mengcheng Zhou Xinfang Zhang Furui Du School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China State Key Laboratory of Automatic Control Technology for Mining and Metallurgy Process Beijing102628China

Residual stress in high-carbon steel affects the dimensional accuracy, structural stability, and integrity of components. Although the evolution of residual stress under an electric field has received extensive attention, its elimination mechanism has not been fully clarified. In this study, it was found that the residual stress of high-carbon steel could be effectively relieved within a few minutes through the application of a low density pulse current. The difference between the current pulse treatment and traditional heat treatment in reducing residual stress is that the electric pulse provides additional Gibbs free energy for the system, which promotes dislocation annihilation and carbon atom diffusion to form carbides, thus reducing the free energy of the system. The electroplastic and thermal effects of the pulse current promoted the movement of dislocations under the electric field, thus eliminating the internal stress caused by dislocation entanglement. The precipitation of carbides reduced the carbon content of the steel matrix and lattice shrinkage, thereby reducing the residual tensile stress. Considering that a pulsed current has the advantages of small size, small power requirement, continuous output, and continuously controllable parameters, it has broad application prospects for eliminating residual stress.

关键词： Residual stress Pulsed electric current Carbide precipitation

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Graph-Neural-Network-Based Transaction Link Prediction Method for Public Blockchain in Heterogeneous Information Networks

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Blockchain: Research and Applications 2025年

作者： Zening Zhao Jinsong Wang Jiajia Wei School of Computer Science and Engineering Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin 300384 China National Engineering Laboratory for Computer Virus Prevention and Control Technology Tianjin 300457 China

Public blockchain has outstanding performance in transaction privacy protection because of its anonymity. The data openness brings feasibility to transaction behavior analysis. At present, the transaction data of the public chain are huge, including complex trading objects and relationships. It is difficult to extract attributes and predict transaction behavior by traditional methods. To solve the problems, we extract the transaction features to construct the Ethereum transaction heterogeneous information network (HIN), and propose graph-neural-network-based transaction prediction method for public blockchain in HINs, which can divide the network into subgraphs according to connectivity and make the prediction results of transaction behavior more accurate. Experiments show that the execution time consumption of the proposed transaction subgraph division method is reduced by 70.61% on average compared with the search method. The accuracy of the proposed behavior prediction method also improve compared with the traditional random walk method, with an average accuracy of 83.82%.

关键词： Blockchain Link prediction Heterogeneous information networks Graph neural networks Random walk

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An Efficient Bitcoin Network Topology Discovery Algorithm for Dynamic Display

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Blockchain: Research and Applications 2025年

作者： Zening Zhao Jinsong Wang Miao Yang Haitao Wang School of Computer Science and Engineering Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin 300384 China National Engineering Laboratory for Computer Virus Prevention and Control Technology Tianjin 300457 China

The Bitcoin network comprises numerous nodes, necessitating users to invest significant network requests and time in comprehending its network topology. In this paper, we propose a Bitcoin network topology discovery algorithm that utilizes lightweight probe nodes to facilitate rapid transmission of network protocols. Building upon this, we introduce a node layer clustering algorithm based on filtering stable network nodes, enabling parallel discovery of the network topology. Additionally, we present an adaptive method for dynamically displaying the layered structure of the network topology. Experimental results demonstrate that our proposed method reduces communication overhead by approximately 72.16% when achieving a 95% similarity in network topology. Furthermore, the algorithm is applicable for discovering the network topology in other blockchain networks with similar structures.

关键词： Blockchain network topology discovery Bitcoin stability coefficient dynamic updates

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