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SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1717-1719页

作者： Jiufang Chen Ye Yuan Xin Luo the College of Computer Science and technology Chongqing University of Posts and TelecommunicationsChongqing 400065 the Chongqing Key Laboratory of Big Data and intelligent computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China the College of Computer and Information Science Southwest UniversityChongqing 400715China IEEE

Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.

关键词： representation preserving undirected

Hybrid Strategy of Partitioned and Monolithic Methods for Solving Strongly Coupled Analysis of Inverse and Direct Piezoelectric and Circuit Coupling

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1371-1386页

作者： Daisuke Ishihara Syunnosuke Nozaki Tomoya Niho Naoto Takayama Department of intelligent and Control Systems Kyushu Institute of TechnologyFukuokaJapan

The inverse and direct piezoelectric and circuit coupling are widely observed in advanced electro-mechanical systems such as piezoelectric energy harvesters.Existing strongly coupled analysis methods based on direct numerical modeling for this phenomenon can be classified into partitioned or monolithic formulations.Each formulation has its advantages and disadvantages,and the choice depends on the characteristics of each coupled problem.This study proposes a new option:a coupled analysis strategy that combines the best features of the existing formulations,namely,the hybrid partitioned-monolithic method.The analysis of inverse piezoelectricity and the monolithic analysis of direct piezoelectric and circuit interaction are strongly coupled using a partitioned iterative hierarchical algorithm.In a typical benchmark problem of a piezoelectric energy harvester,this research compares the results from the proposed method to those from the conventional strongly coupled partitioned iterative method,discussing the accuracy,stability,and computational cost.The proposed hybrid concept is effective for coupled multi-physics problems,including various coupling conditions.

关键词： Structure-piezoelectric-circuit interaction energy harvesting partitioned method monolithic method hybrid method

Application of electromagnetic metallurgy in continuous casting: A review

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Progress in Natural Science:Materials International 2024年第1期34卷 1-11页

作者： Jiale Li Yi Nian Xiang Liu Youcheng Zong Xinyu Tang Chaojie Zhang Liqiang Zhang The intelligent Metallurgy Research institute School of Metallurgical Engineering Anhui University of Technology

The standards within the global steel industry are constantly advancing, necessitating increasingly rigorous quality control protocols during the continuous casting process. Central to the challenges faced in this domain are persistent defects such as central segregation, V-shaped segregation, and center porosity, which significantly impede the production of high-caliber steel products. The discipline of electromagnetic metallurgy has emerged as a critical solution in reducing these defects, thereby enhancing the efficiency and stability of continuous casting operations. Its demonstrated effectiveness has led to its widespread implementation across global and domestic steel production industries. This paper aims to deliver a comprehensive examination of electromagnetic metallurgy's impact on the final stages of solidification in continuous casting, along with its contributions to the heating and purification processes within the tundish. Additionally, it will explore the potential advancements and applications of this technology in the evolving sphere of continuous casting.

关键词： continuous casting Quality control Final electromagnetic stirring Induction heating Electromagnetic purification

One-step hydrothermal synthesis of few-layered metallic phase MoS2 for high-performance supercapacitors

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Progress in Natural Science:Materials International 2024年第2期34卷 429-436页

作者： Jing Xu Xulong Yuan Yujie Zhao Shaoqi Rui Qingling Jia Han Li Shun Lu Bing Li Yongxing Zhang Xuebin Zhu Anhui Province Key Laboratory of Pollutant Sensitive Materials and Environmental Remediation Anhui Province Key Laboratory of Intelligent Computing and Applications Anhui Province Industrial Generic Technology Research Center for Alumics Materials Huaibei Normal University Chongqing institute of Green and intelligent technology Chinese Academy of Sciences Key Laboratory of Materials Physics Institute of Solid State Physics HFIPS Chinese Academy of Sciences

In recent years,molybdenum disulfide（MoS2） has gained significant attention in the scientific community.Fewlayered MoS2demonstrates unique properties and potential applications.However,the synthesis of few-layered and high-purity 1T-MoS2is still a challenge.In this study,we successfully employed a hydrothermal method to synthesize few-layered and high-purity 1T-MoS2.The purity of the material is controlled by a combination of sodium borohydride and ethanol.Notably,the few-layered 1T-MoS2exhibits exceptional performance as a supercapacitor,including the high specific capacitance(250.3 F g-1at a current density of 1 A g-1) and excellent long-trem cycling stability（90.7 % after 5000 cycles）.Meanwhile,the asymmetric device assembled by 6-FL-1TMoS2and active carbon on carbon cloths exhibits excellent flexibility and high energy and power density(23.1μWh cm-2at 600 μW cm-2,55 μWh cm-2at 12000 μW cm-2).This work provides valuable insights into the synthesis of few-layered and high-purity 1T-MoS2,opening up new avenues for further research and applications.

关键词： 1T-MoS2 Few-layered High-purity One-pot hydrothermal method Supercapacitor

Organic thin-film transistors and related devices in life and health monitoring

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Nano Research 2024年第2期17卷 426-444页

作者： Chenfang Sun Tie Wang Tianjin Key Laboratory of Drug Targeting and Bioimaging Life and Health Intelligent Research InstituteTianjin University of TechnologyTianjin 300384China

The early determination of disease-related biomarkers can significantly improve the survival rate of patients.Thus,a series of explorations for new diagnosis technologies,such as optical and electrochemical methods,have been devoted to life and health monitoring.Organic thin-film transistor(OTFT),as a state-of-the-art nano-sensing technology,has attracted significant attention from construction to application owing to the merits of being label-free,low-cost,facial,and rapid detection with multi-parameter responses.Nevertheless,interference from non-specific adsorption is inevitable in complex biological samples such as body liquid and exhaled gas,so the reliability and accuracy of the biosensor need to be further improved while ensuring sensitivity,selectivity,and stability.Herein,we overviewed the composition,mechanism,and construction strategies of OTFTs for the practical determination of disease-related biomarkers in both body fluids and exhaled gas.The results show that the realization of bio-inspired applications will come true with the rapid development of high-effective OTFTs and related devices.

关键词： organic thin-film transistors biosensors biomarkers organic bioelectronics organic semiconductors healthcare

An evolutionary multiobjective method based on dominance and decomposition for feature selection in classification

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Science China(Information Sciences) 2024年第2期67卷 5-19页

作者： Jing LIANG Yuyang ZHANG Ke CHEN Boyang QU Kunjie YU Caitong YUE Ponnuthurai Nagaratnam SUGANTHAN School of Electrical and Information Engineering Zhengzhou University State Key Laboratory of intelligent Agricultural Power Equipment School of Electrical Engineering and Automation Henan Institute of Technology School of Electronics and Information Zhongyuan University of Technology KINDI Center for computing Research College of EngineeringQatar University

Feature selection in classification can be considered a multiobjective problem with the objectives of increasing classification accuracy and decreasing the size of the selected feature subset. Dominance-based and decomposition-based multiobjective evolutionary algorithms(MOEAs) have been extensively used to address the feature selection problem due to their strong global search capability. However, most of them face the problem of not effectively balancing convergence and diversity during the evolutionary process. In addressing the aforementioned issue, this study proposes a unified evolutionary framework that combines two search forms of dominance and decomposition. The advantages of the two search methods assist one another in escaping the local optimum and inclining toward a balance of convergence and diversity. Specifically, an improved environmental selection strategy based on the distributions of individuals in the objective space is presented to avoid duplicate feature subsets. Furthermore, a novel knowledge transfer mechanism that considers evolutionary characteristics is developed, allowing for the effective implementation of positive knowledge transfer between dominance-based and decomposition-based feature selection methods. The experimental results demonstrate that the proposed algorithm can evolve feature subsets with good convergence and diversity in a shorter time compared with 9 state-of-the-art feature selection methods on 20 classification problems.

关键词： evolutionary algorithms feature selection multiobjective optimization knowledge transfer classification

Learning Scalable Task Assignment with Imperative-Priori Conflict Resolution in Multi-UAV Adversarial Swarm Defense Problem

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Journal of Systems Science & Complexity 2024年第1期37卷 369-388页

作者： ZHAO Zhixin CHEN Jie XIN Bin LI Li JIAO Keming ZHENG Yifan School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Shanghai institute of intelligent Science and technology Tongji UniversityShanghai 201804China School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous intelligent Unmanned Systems Beijing 100081China Shanghai institute of intelligent Science and technology Tongji UniversityShanghai 201804China.

The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV swarm.Decomposing the problem into task assignment and low-level interception strategies is a widely used approach.Learning-based approaches for task assignment are a promising direction.Existing studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict resolution.In contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to scalability.To achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment method for sensor target coverage problem,a scalable centralized assignment method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is proposed.Then,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free assignment.Further,the IPCR mechanism is parallelized to enable efficient training.To validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various scales.The experimental results show that the proposed algorithm not only achieves conflict-free task assignment but also maintains scalability,and significantly improve the success rate of defense.

关键词： Conflict resolution reinforcement learning scalability task assignment.

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Privacy Preserving Algorithm for Spectrum Sensing in Cognitive Vehicle Networks

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Chinese Journal of Electronics 2024年第1期33卷 30-42页

作者： Hongning LI Tonghui HU Jiexiong CHEN Xiuqiang WU Qingqi PEI Guangzhou institute of technology Xidian University Guangzhou CEPREI Shaanxi Key Laboratory of Blockchain and Secure computing

The scarcity of spectrum resources fails to meet the increasing throughput demands of vehicular networks. There is an urgent need to maximize the utilization of spectrum bands in mobile networks. To ascertain the availability of spectrum bands, users should engage in wireless channel sensing and collaboration. However, spectrum sensing data always involves users’ privacy, such as their location. This paper first introduces sensing trajectory inference attack in cognitive vehicular networks and then proposes a data confusion-based privacy-preserving algorithm and a cryptonym array-based privacy-preserving aggregation scheme for spectrum sensing in cognitive vehicular networks. Unlike existing methods, the proposed schemes transmit confused data during the aggregation process. This deliberate obfuscation makes it almost impossible to infer users’ location from the transmitted data. The analysis demonstrates the resilience of the proposed schemes against sensing trajectory inference attack.

关键词： Location privacy preservation Cognitive radio network Cooperative spectrum sensing

Distributed collaborative complete coverage path planning based on hybrid strategy

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Journal of Systems Engineering and Electronics 2024年第2期35卷 463-472页

作者： ZHANG Jia DU Xin DONG Qichen XIN Bin School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.

关键词： multi-agent cooperation unmanned aerial vehicles(UAV) distributed algorithm complete coverage path planning(CCPP)

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