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Journal of Iron and Steel Research International 2025年第1期32卷 171-185页

作者： Chi-hao Yu Hong-jiang Pan Yan-ping Zhao De-ting Tang Hai-jun Wang Faculty of Materials Science and engineering Kunming University of Science and TechnologyKunming650093YunnanChina school of Electronics and information engineering Anshun UniversityAnshun561000GuizhouChina school of Metallurgical engineering Anhui University of TechnologyMa’anshan243032AnhuiChina

Over the years,the high magnetic induction of industrial Mn-added electrical steel is assumed to be the enhancement of{100}texture derived from its austenite-ferrite phase transformation during hot rolling(phase transformation(PT)method).However,it is still undetermined without straightforward experimental *** reason for{100}texture improvement of Mn-added electrical steel is experimentally confirmed due to the recrystallization induced by the austenite-ferrite phase transformation during hot ***,a more promising methodology to further improve{100}texture and formability of hot-rolled electrical steel is promoted by the control of hot rolling deformation condition(shear deformation(SD)method).The results show that the nucleation mechanisms of{100}oriented recrystallized grains are different in the samples by SD and PT methods,which are in-depth shear deformation and austenite-ferrite phase transformation,*** this case,coarse{100}oriented recrystallized grains and low residual stress are obtained in the sample by SD method,which is responsible for its superior{100}texture and *** contrast,the sample by PT method forms fine recrystallized grains with random orientations and accumulates severe residual stress.

关键词： Non-oriented electrical steel {100}texture Formability Austenite-ferrite phase transformation Shear deformation

A Correntropy-Based Echo State Network With Application to Time Series Prediction

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 425-435页

作者： Xiufang Chen Zhenming Su Long Jin Shuai Li the school of information Science and engineering Lanzhou University IEEE the Hangzhou Institute for Advanced Study University of Chinese Academy of Science

As a category of recurrent neural networks, echo state networks(ESNs) have been the topic of in-depth investigations and extensive applications in a diverse array of fields, with spectacular triumphs achieved. Nevertheless, the traditional ESN and the majority of its variants are devised in the light of the second-order statistical information of data(e.g., variance and covariance), while more information is neglected. In the context of information theoretic learning, correntropy demonstrates the capacity to grab more information from data. Therefore, under the guidelines of the maximum correntropy criterion, this paper proposes a correntropy-based echo state network(CESN) in which the first-order and higher-order information of data is captured, promoting robustness to noise. Furthermore, an incremental learning algorithm for the CESN is presented, which has the expertise to update the CESN when new data arrives, eliminating the need to retrain the network from scratch. Finally, experiments on benchmark problems and comparisons with existing works are provided to verify the effectiveness and superiority of the proposed CESN.

关键词： Correntropy echo state network (ESN) noise time series prediction

Event-triggered leader-follower bipartite consensus control for nonlinear multi-agent systems under DoS attacks

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Science China(information Sciences) 2025年

作者： Wei SU Chaoxu MU Song ZHU Ben NIU Changyin SUN school of control Science and engineering Tianjin University school of Mathematics China University of Mining and Technology school of control Science and engineering Dalian University of Technology school of Automation Southeast University

Aiming at the consensus control problem of nonlinear multi-agent systems (MASs) under directed topology, a leader-follower bipartite consensus control strategy is proposed. This strategy takes into account the potential for denial-ofservice (DoS) attacks and completely unknown system dynamics. Specifically, the bipartite consensus dynamics describes the cooperation and competition relationship between followers and the leader, that is, the follower chooses to move in accordance with or opposite to the leader according to its trajectory. In order to optimize the communication bandwidth and mitigate the impact of DoS attacks, the proposed consensus control scheme integrates the DoS attack detection mechanism and eventtriggered mechanism. In addition, neural networks (NNs) are used to solve the nonlinear problem, and a speed function is designed to achieve the desired tracking performance, ensuring that all agents’ tracking errors converge to a predefined set in a finite time. With the help of backstepping, graph theory, and Lyapunov stability theory, sufficient conditions for achieving bipartite consensus without Zeno behavior are established. Finally, the accuracy and feasibility of the theoretical analysis are verified by simulation cases.

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the school of control Science and engineering Shandong University IEEE the school of Electronic and Electrical engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System control and information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

Characterization of size-resolved aerosol hygroscopicity and liquid water content in Nanjing of the Yangtze River Delta

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Journal of Environmental Sciences 2025年第5期151卷 26-41页

作者： Youling Jiang Yan Ma Jun Zheng Nan Ye Cheng Yuan school of Environmental Science and engineering Nanjing University of Information Science and TechnologyNanjing 210044China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044China school of Emergency Management Nanjing University of Information Science&TechnologyNanjing 210044China

Aerosol hygroscopicity and liquid water content(ALWC)have important influences on the environmental and climate effect of *** this study,we measured the hygroscopic growth factors(GF)of particles with dry diameters of 40,80,150,and 200 nm during the wintertime in *** the GF-derived hygroscopicity parameter(κ_(gf))and ALWC increased with particle size,but displayed differing diurnal variations,withκ_(gf)peaking around the midday,while ALWC peaking in the early ***,ammonium and oxygenated organic aerosols(OOA)were found as the chemical components mostly strongly correlated with ALWC.A closure study suggests that during midday photo-oxidation and nighttime high ALWC periods,theκof organic aerosols(κ_(org))was underestimated when using previous ***,we re-constructed parameterizations forκ_(org)and the oxidation level of organics for these periods,which indicates a higher hygroscopicity of photochemically formed OOA than the aqueous OOA,yet both being much higher than the generally assumed OOA ***,in a typical high ALWC episode,concurrently increased ALWC,nitrate,OOA as well as aerosol surface area and mass concentrations were observed under elevated ambient *** strongly indicates a coupled effect that the hygroscopic secondary aerosols,in particular nitratewith strong hygroscopicity,led to large increase in ALWC,which in turn synergistically boosted nitrate and OOA formation by heterogeneous/aqueous *** interaction may represent an important mechanism contributing to enhanced formation of secondary aerosols and rapid growth of fine particulate matter under relatively high RH conditions.

关键词： Aerosol hygroscopicity Aerosol liquid water content Photo-oxidation Aqueous/heterogeneous reactions

FedCLCC:A personalized federated learning algorithm for edge cloud collaboration based on contrastive learning and conditional computing

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Defence Technology(防务技术) 2025年第1期43卷 80-93页

作者： Kangning Yin Xinhui Ji Yan Wang Zhiguo Wang school of information and Software engineering University of Electronic Science and Technology of ChinaChengdu611731China Institute of Public Security Kash Institute of Electronics and Information IndustryKashi844000China

Federated learning(FL)is a distributed machine learning paradigm for edge cloud *** can facilitate data-driven decision-making in tactical scenarios,effectively addressing both data volume and infrastructure challenges in edge ***,the diversity of clients in edge cloud computing presents significant challenges for *** federated learning(pFL)received considerable attention in recent *** example of pFL involves exploiting the global and local information in the local *** pFL algorithms experience limitations such as slow convergence speed,catastrophic forgetting,and poor performance in complex tasks,which still have significant shortcomings compared to the centralized *** achieve high pFL performance,we propose FedCLCC:Federated Contrastive Learning and Conditional *** core of FedCLCC is the use of contrastive learning and conditional *** learning determines the feature representation similarity to adjust the local *** computing separates the global and local information and feeds it to their corresponding heads for global and local *** comprehensive experiments demonstrate that FedCLCC outperforms other state-of-the-art FL algorithms.

关键词： Federated learning Statistical heterogeneity Personalized model Conditional computing Contrastive learning

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Generalized susceptibilities of the net-baryon number based on the three-dimensional Ising universality class

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Chinese Physics C 2025年第02期 158-166页

作者：潘雪 school of Electronic information and Electrical engineering Chengdu University

Assuming the equilibrium of the Quantum Chromodynamics（QCD） system, we investigate the critical behavior of the sixth-, eighth-, and tenth-order susceptibilities of the net-baryon number through mapping the results in the three-dimensional Ising model to that of QCD. Both the leading and sub-leading critical contributions from the Ising model are discussed. When considering only the leading critical contribution, the density plots of susceptibilities of the same order demonstrate a consistent general pattern independent of the values of the mapping *** the critical point is approached from the crossover side, a negative dip followed by a positive peak is observed in the μBdependence of the three different orders of susceptibilities. When sub-leading critical contribution is considered, modifications become apparent in the density plots of the susceptibilities. The emergence of negative dips in the μBdependence of the susceptibilities is not an absolute phenomenon, whereas the positive peak structure is a more robust feature of the critical point.

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Data Gathering Based on Hybrid Energy Efficient Clustering Algorithm and DCRNN Model in Wireless Sensor Network

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China Communications 2025年第03期 115-131页

作者： Li Cuiran Liu Shuqi Xie Jianli Liu Li school of Electronic and information engineering Lanzhou Jiaotong University

In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN) caused by uneven energy consumption among nodes, a hybrid energy efficient clustering routing base on firefly and pigeon-inspired algorithm(FF-PIA) is proposed to optimise the data transmission path. After having obtained the optimal number of cluster head node(CH), its result might be taken as the basis of producing the initial population of FF-PIA algorithm. The L′evy flight mechanism and adaptive inertia weighting are employed in the algorithm iteration to balance the contradiction between the global search and the local search. Moreover, a Gaussian perturbation strategy is applied to update the optimal solution, ensuring the algorithm can jump out of the local optimal solution. And, in the WSN data gathering, a onedimensional signal reconstruction algorithm model is developed by dilated convolution and residual neural networks(DCRNN). We conducted experiments on the National Oceanic and Atmospheric Administration(NOAA) dataset. It shows that the DCRNN modeldriven data reconstruction algorithm improves the reconstruction accuracy as well as the reconstruction time performance. FF-PIA and DCRNN clustering routing co-simulation reveals that the proposed algorithm can effectively improve the performance in extending the network lifetime and reducing data transmission delay.

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DDPG-Based Intelligent Computation Offloading and Resource Allocation for LEO Satellite Edge Computing Network

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China Communications 2025年第03期 1-15页

作者： Jia Min Wu Jian Zhang Liang Wang Xinyu Guo Qing school of Electronics and information engineering Harbin Institute of Technology

Low earth orbit(LEO) satellites with wide coverage can carry the mobile edge computing(MEC)servers with powerful computing capabilities to form the LEO satellite edge computing system, providing computing services for the global ground users. In this paper, the computation offloading problem and resource allocation problem are formulated as a mixed integer nonlinear program(MINLP) problem. This paper proposes a computation offloading algorithm based on deep deterministic policy gradient(DDPG)to obtain the user offloading decisions and user uplink transmission power. This paper uses the convex optimization algorithm based on Lagrange multiplier method to obtain the optimal MEC server resource allocation scheme. In addition, the expression of suboptimal user local CPU cycles is derived by relaxation method. Simulation results show that the proposed algorithm can achieve excellent convergence effect, and the proposed algorithm significantly reduces the system utility values at considerable time cost compared with other algorithms.

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Optimization of transverse unidirectional scattering by morphology modification of irregular V-shaped silicon nanoantennas

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Optoelectronics Letters 2025年第3期21卷 129-135页

作者： ZENG Ming ZHAO Feng WANG Xianghui school of Electrical and information engineering Tianjin University Institute of Modern Optics Tianjin Key Laboratory of Micro-scale Optical Information Science and TechnologyNankai University

A scheme based on irregular V-shaped silicon nanoantennas is proposed to optimize transverse unidirectional scattering under plane wave irradiation. Traditional methods of designing regular shapes offer fewer parameters and higher search efficiency. However, due to the limitations of regular shapes, it is challenging to meet high-precision design requirements. Irregular shape design allows for a broader range of adjustments, but the complexity of shape parameters leads to lower search efficiency and a higher likelihood of converging to local optima.

关键词： A