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CMAGAN:classifier-aided minority augmentation generative adversarial networks for industrial imbalanced data and its application to fault prediction

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Advances in Manufacturing 2024年第3期12卷 603-618页

作者： Wen-Jie Wang Zhao liu ping Zhu School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China National Engineering Research Center of Automotive Power and Intelligent Control Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China School of Design Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China

Class imbalance is a common characteristic of industrial data that adversely affects industrial data mining because it leads to the biased training of machine learning *** address this issue,the augmentation of samples in minority classes based on generative adversarial networks(GANs)has been demonstrated as an effective *** study proposes a novel GAN-based minority class augmentation approach named classifier-aided minority augmentation generative adversarial network(CMAGAN).In the CMAGAN framework,an outlier elimination strategy is first applied to each class to minimize the negative impacts of ***,a newly designed boundary-strengthening learning GAN(BSLGAN)is employed to generate additional samples for minority *** incorporating a supplementary classifier and innovative training mechanisms,the BSLGAN focuses on learning the distribution of samples near classification ***,it can fully capture the characteristics of the target class and generate highly realistic samples with clear ***,the new samples are filtered based on the Mahalanobis distance to ensure that they are within the desired *** evaluate the effectiveness of the proposed approach,CMAGAN was used to solve the class imbalance problem in eight real-world fault-prediction *** performance of CMAGAN was compared with that of seven other algorithms,including state-of-the-art GAN-based methods,and the results indicated that CMAGAN could provide higher-quality augmented results.

关键词： Class imbalance Minority class augmentation Generative adversarial network(GAN) Boundary strengthening learning(BSL) Fault prediction

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Understanding microstructure-property relationships of HPDC Al-Si alloy based on machine learning and crystal plasticity simulation

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Advances in Manufacturing 2024年第3期12卷 497-511页

作者： Qiang-Qiang Zhai Zhao liu ping Zhu State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China National Engineering Research Center of Automotive Power and Intelligent Control Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China School of Design Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China

Al-Si alloys manufactured via high-pressure die casting(HPDC)are suitable for a wide range of ***,the heterogeneous microstructure and unpredictable pore distribution of Al-Si high-pressure die castings result in significant variations in the mechanical properties,thus leading to a complicated microstructure-property relationship that is difficult to ***,a computational framework incorporating machine learning and crystal plasticity method is *** framework aims to provide a systematic and comprehensive understanding of this relationship and enable the rapid prediction of macroscopic mechanical properties based on the ***,we select eight variables that can effectively characterize the microstructural features and then obtain their statistical ***,based on 160 samples obtained via the Latin hypercube sampling method,representative volume elements are constructed,and the crystal plasticity fast Fourier transformation method is executed to obtain the macroscopic mechanical ***,the yield strength,elastic modulus,strength coefficient,and strain-hardening exponent are used to characterize the stress-strain curve,and Gaussian process regression models and microstructural variables are ***,sensitivity and univariate analyses based on these machine-learning models are performed to obtain insights into the microstructure-property relationships of the HPDC Al-Si *** results show that the Gaussian process regression models exhibit high accuracy(R2 greater than 0.84),thus confirming the viability of the proposed *** results of sensitivity analysis indicate that the pore size exerts the most significant effect on the mechanical ***,the proposed framework can not only be transferred to other alloys but also be employed for material design.

关键词： High-pressure die casting(HPDC) Machine learning Crystal plasticity Aluminum alloys

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Graphene oxide/Al_(2)O_(3)-based diffusive memristor cells:enabling robust crossbar arrays for multidisciplinary applications

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Rare Metals 2024年第8期43卷 3997-4005页

作者： Chen liu Jun-Cheng Jin Yi-Ke Xiao xin-xin Wang ping-Yuan Yan Yan-Qiang Cao Li-Yong Jiang Chuan-Xiang Sheng Ye-Feng Yu School of Microelectronics Nanjing University of Science and TechnologyNanjing 210094China School of Science Nanjing University of Science and TechnologyNanjing210094China School of Information Science and Technology Fudan UniversityShanghai 200433China

A memristor crossbar array (MCA) has emerged as a cutting-edge platform for advanced memory and neuromorphic computing hardware,offering unrivaled bit-level storage density.A diffusive memristor cell (DMC) is particularly well-suited for MCA integration due to its inherent threshold switching characteristics as a selector,effectively addressing current sneak path *** DMC's potential is acknowledged,it necessitates furtherexploration of their practical applicability.

关键词： crossbar arrays offering

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Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries

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Nano-Micro Letters 2024年第9期16卷 13-48页

作者： Yunnan Gao Ling liu Yi Jiang Dexin Yu Xiaomei Zheng Jiayi Wang Jingwei liu Dan Luo Yongguang Zhang Zhenjia Shi xin Wang Ya‑ping Deng Zhongwei Chen Power Battery and Systems Research Center State Key Laboratory of CatalysisDalian Institute of Chemical PhysicsDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023People’s Republic of China Department of Chemical Engineering University of WaterlooWaterlooON N2L 3G1Canada Institute of Carbon Neutrality Zhejiang Wanli UniversityNingbo 315100People’s Republic of China College of Materials and Chemistry China Jiliang UniversityHangzhou 310018People’s Republic of China

Zinc-air batteries(ZABs)are promising energy storage systems because of high theoretical energy density,safety,low cost,and abundance of ***,the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ***,feasible and advanced non-noble-metal elec-trocatalysts for air cathodes need to be identified to promote the oxygen catalytic *** this review,we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this ***,we discussed the work-ing mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design,crystal structure tuning,interface strategy,and atomic *** also included theoretical studies,machine learning,and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox ***,we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

关键词： Zinc-air batteries Bifunctional electrocatalysts Design principles Mechanistic understandings

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Reconstruction of biomimetic ionic channels within covalent organic frameworks for ultrafast and selective uranyl capture

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Science China Chemistry 2024年第10期67卷 3423-3431页

作者： Cheng-Rong Zhang Xiao-Juan Chen Cheng-Peng Niu Cheng Meng Shun-Mo Yi xin liu Jia-xin Qi Qiu-Xia Luo Ru-ping Liang Jian-Ding Qiu State Key Laboratory of Nuclear Resources and Environment East China University of TechnologyNanchang 330013China College of Chemistry and Chemical Engineering Nanchang UniversityNanchang 330031China

The efficient extraction of uranium,as the primary component of nuclear energy,holds significant *** inspiration from the charge interaction observed in biological ion channels,we encapsulated negatively charged polystyrene sulfonate(PSS)or sodium polystyrene carboxylate(PVBA)into the nanochannels of amidoxime functionalized covalent organic framework(COF-AO)in-situ to alter the cavity environment of *** synthesized COF-AO-PSS and COF-AO-PVBA are used for ultra-fast and highly selective uranium *** negatively charged PSS/PVBA was confined in the COF-AO channel providing the driving force for uranium transport and blocking other ions,thus creating a highly selective“uranium highway”.Additionally,introducing sulfonate groups or carboxyl groups into COF-AO offers supplementary coordination environments and weak interactions with *** to charge-assisted migration and various interaction mechanisms,both COF-AO-PSS and COF-AO-PVBA exhibit faster adsorption kinetics and higher selectivity compared to COF-AO *** adsorption capacities are 3.8 times and 2.4 times that of COF-AO alone respectively which highlights the necessity for constructing biomimetic ion channels in uranium adsorption *** work presents a bionic adsorbent based on covalent organic frameworks(COFs)for the first time,overcoming environmental and equipment limitations associated with traditional photocatalysis and electrocatalysis methods for uranium capture,opening up new avenues for designing multifunctional materials that mimic biological systems.

关键词： covalent organic frameworks Uranium biomimetic ion-channels adsorption

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Quantitative method for calculating spatial release region for laser-guided bomb

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Journal of Systems Engineering and Electronics 2024年第4期35卷 1053-1062页

作者： YANG ping XIAO Bing CHEN xin HAO Yuntao Air Force Early Warning Academy Wuhan 430019China Unit 93175 of the PLA Changchun 136000China

The laser-guided bomb(LGB)is an air-to-ground pre-cision-guided weapon that offers high hit rates,great power,and ease of *** are guided by semi-active laser ground-seek-ing technology,which means that atmospheric conditions can affect their *** spatial release region(SRR)of LGBs is difficult to calculate precisely,especially when there is a poor field of *** can result in a lower real hit *** increase the hit probability of LGBs in tough atmospheric situa-tions,a novel method for calculating the SRR has been *** method is based on the transmittance model of the 1.06μm laser in atmospheric species and the laser diffuse reflection model of the target surface to determine the capture target time of the laser ***,it calculates the boundary ballistic space starting position by ballistic model and gets the spatial scope of the spatial release *** method can determine the release region of LGBs based on flight test data such as instantaneous velocity,altitude,off-axis angle,and atmospheric *** more effectively employing aircraft release conditions,atmospheric visibility and other factors,the SRR calculation method can improve LGB hit probabi-lity by 9.2%.

关键词： laser-guided bombs(LGBs) hit probability atmo-spheric transmittance spatial release region(SRR)boundary ballistic

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Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

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International Journal of Minerals,Metallurgy and Materials 2024年第1期31卷 106-117页

作者： xin Shao Qing liu Zicheng xin Jiangshan Zhang Tao Zhou Shaoshuai Li State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China Engineering Research Center of MES Technology for Iron&Steel Production Ministry of EducationBeijing 100083China Laiwu Iron and Steel Group Yinshan Section Steel Co. Ltd.Jinan 271104China

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

关键词： basic oxygen furnace oxygen consumption oxygen blowing time oxygen balance mechanism deep neural network hybrid model

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Plastic deformation behavior of a Cu-10Ta alloy under strong impact loading

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Defence Technology（防务技术） 2024年第2期32卷 368-382页

作者： ping Song Jianghai liu Wenbin Li Yiming Li Research Institute of Chemical Defense Academy of Military ScienceBeijing102205China Ministerial Key Laboratory of ZNDY Nanjing University of Science and TechnologyNanjing210094China

In this work,a Cu-10Ta alloy with a copper to tantalum mass ratio of 9:1 is prepared using powder metallurgy *** properties of the alloy,including density,microstructure,melting point,and constant-volume specific heat,are *** the split Hopkinson pressure bar(SHPB)and flyerplate impact experiments,the relationship between equivalent stress and equivalent plastic strain of the material is studied at temperatures of 298-823 K and under strain rates of 1×10^(-3)-5.2×10^(3)s^(-1),and the Hugoniot relationship at impact pressures of 1.46-17.25 GPa and impact velocities of 108-942 m/s is *** of the Cu-10Ta microstructure that occurs during high-strain-rate impact is *** indicate that the Cu-10Ta alloy possesses good thermal stability,and at ambient temperatures of up to 50%its melting point,stress softening of less than 15%of the initial strength is observed.A modified J-C constitutive model is employed to accurately predict the variation of yield strength with strain *** strong impact,the copper phase is identified as the primary source of plastic deformation in the Cu-10Ta alloy,while significant deformation of the high-strength tantalum particles is less ***,the longitudinal wave speed D is found to correlate linearly with the particle velocity u upon strong *** reveals that the sound speed and spallation strength of the alloy increase with increasing impact pressure.

关键词： Cu-10Ta SHPB Plastic deformation Flyer impact Hugoniot relationship

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Advancements in S-scheme heterojunction materials for photocatalytic environmental remediation

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Journal of Materials Science & Technology 2024年第2期169卷 182-198页

作者： Changliang Nie Xiaohan Wang ping Lu Yukun Zhu xin Li Hua Tang School of Environmental Science and Engineering State Key Laboratory of Bio-fibers and Eco-textilesQingdao UniversityQingdao266071China Institute of Biomass Engineering Key Laboratory of Energy Plants Resource and UtilizationMinistry of Agriculture and Rural AffairsSouth China Agricultural UniversityGuangzhou510642China School of Environmental Science and Engineering Shandong UniversityQingdao266237China

Recently,S-scheme heterojunctions have gained considerable attention in the field of photocatalytic environmental remediation as their potential to achieve efficient spatial charge separation coupled with strong redox ***,this review provides an overview of the current state-of-the-art in the development of S-scheme-based photocatalysts for the purification of environmental *** review first covers the fundamentals of heterogeneous photocatalysis for environmental ***,an introduction to the background,mechanism,design principles,and characterization techniques of S-scheme heterojunctions is ***,the review presents a comparison and summary of using various S-scheme photocatalysts for the removal of several target pollutants,such as bacteria,heavy metals,nitrogen oxides,antibiotics,and ***,the modification strategies of S-scheme heterojunction photocatalysts are also ***,a brief discussion of the challenges and prospects associated with S-scheme photocatalytic systems is demonstrated.

关键词： S-scheme heterojunctions Photocatalyst Pollutant Environmental remediation

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Collision-free parking recommendation based on multi-agent reinforcement learning in vehicular crowdsensing

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Digital Communications and Networks 2024年第3期10卷 609-619页

作者： xin Li xinghua Lei Xiuwen liu Hang Xiao College of Computer Science and Technology China University of Petroleum(East China)QingDao266580China

The recent proliferation of Fifth-Generation(5G)networks and Sixth-Generation(6G)networks has given rise to Vehicular Crowd Sensing(VCS)systems which solve parking collisions by effectively incentivizing vehicle ***,instead of being an isolated module,the incentive mechanism usually interacts with other *** on this,we capture this synergy and propose a Collision-free Parking Recommendation(CPR),a novel VCS system framework that integrates an incentive mechanism,a non-cooperative VCS game,and a multi-agent reinforcement learning algorithm,to derive an optimal parking strategy in real ***,we utilize an LSTM method to predict parking areas roughly for recommendations *** incentive mechanism is designed to motivate vehicle participation by considering dynamically priced parking tasks and social network *** order to cope with stochastic parking collisions,its non-cooperative VCS game further analyzes the uncertain interactions between vehicles in parking *** its multi-agent reinforcement learning algorithm models the VCS campaign as a multi-agent Markov decision process that not only derives the optimal collision-free parking strategy for each vehicle independently,but also proves that the optimal parking strategy for each vehicle is ***,numerical results demonstrate that CPR can accomplish parking tasks at a 99.7%accuracy compared with other baselines,efficiently recommending parking spaces.

关键词： Incentive mechanism Non-cooperative VCS game Multi-agent reinforcement learning Collision-free parking strategy Vehicular crowdsensing

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