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Non-Isothermal Dissolutive Wetting of Al-Ni and Cu-Ni Alloy Nanodroplets on a Cu(100)Substrate

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Journal of Thermal Science 2022年第4期31卷 1135-1144页

作者： wang shaoyu wang Zijie wang Shuolin YANG Yanru HUANG Congliang wang Xiaodong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Research Center of Engineering Thermophysics North China Electric Power University Beijing 102206China School of Electrical and Power Engineering China University of Mining and Technology Xuzhou 221116China

The kinetics of Al-Ni and Cu-Ni nanodroplets spreading over a Cu substrate in the presence of a temperature difference between them is studied via molecular dynamics *** simulations show that significant dissolution reactions occur for the two systems and there is no precursor film generated during *** spreading rate significantly increases when nanodroplets contain less Ni atoms in the Al-Ni/Cu wetting ***,a different trend is observed in the Cu-Ni/Cu wetting *** spreading rate remains unchanged regardless of the ratio of Cu to Ni atoms owing to the fact that Cu and Ni have almost the same lattice *** simulations also demonstrate that,because of the temperature gradient between the nanodroplet and substrate,local solidification takes place in the later spreading stage,which significantly hinders *** to the mismatch of lattice constants between Al and the Cu atoms in the Al-Ni/Cu wetting systems,hexagonal closest packed(hcp),body centered cubic(bcc),and face centered cubic(fcc)arrangements of atoms are observed when the Al-Ni nanodroplets solidify completely,whereas there is only a fcc arrangement in the Cu-Ni/Cu wetting systems.

关键词： spreading mechanism non-isothermal solidification molecular dynamics simulations

A Physical Layer Authentication Mechanism for IoT Devices

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China Communications 2022年第5期19卷 129-140页

作者： Xinglu Li Kaizhi Huang shaoyu wang Xiaoming Xu PLA Strategic Support Force Information Engineering University Zhengzhou 450001China

When Internet of Things(IoT)nodes access the network through wireless channels,the network is vulnerable to spoofing attacks and the Sybil ***,the connection of massive devices in IoT makes it difficult to manage and distribute keys,thus limiting the application of traditional high-level authentication *** with the high-level authentication scheme,the physical layer authentication scheme realizes the lightweight authentication of users by comparing the wireless channel characteristics of adjacent ***,traditional physical layer authentication schemes still adopt the one-to-one authentication method,which will consume numerous network resources in the face of large-scale IoT node access *** order to realize the secure access authentication of IoT nodes and regional intrusion detection with low resource consumption,we propose a physical layer authentication mechanism based on convolution neural network(CNN),which uses the deep characteristics of channel state information(CSI)to identify sending nodes in different ***,we obtain the instantaneous CSI data of IoT sending nodes at different locations in the pre-set area,and then feed them into CNN for training to procure a model for IoT node *** its powerful ability of data analysis and feature extraction,CNN can extract deep Spatio-temporal environment features of CSI data and bind them with node ***,an authentication mechanism which can distinguish the identity types of IoT nodes located in different positions is established to authenticate the identity of unknown nodes when they break into the pre-set *** results show that this authentication mechanism can still achieve 94.7%authentication accuracy in the case of a low signalto-noise ratio(SNR)of 0 dB,which means a significant improvement in authentication accuracy and robustness.

关键词： IoT CSI CNN access authentication intrusion detection

Dynamic performance of linear electromagnetic actuators in a stray magnetic field:theoretical analysis and experimental verification

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Plasma Science and Technology 2022年第12期24卷 213-222页

作者： Rumeng wang Yong YANG shaoyu wang Ming ZHANG International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and TechnologySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People's Republic of China

Linear electromagnetic actuators(LEAs) are widely used in tokamaks,but they are extremely sensitive to and are prone to fail in a high-strength stray magnetic field(SMF),which is usually a concomitant with *** this paper,a multi-physics coupling analysis model of LEA,including magnetic field,electric circuit and mechanical motion,is proposed,and the dynamic characteristics of LEAs in SMFs are studied in detail based on the proposed *** failure mechanism of LEAs in SMFs is revealed,and the influence of SMFs on the dynamic performance of LEAs is studied and *** is shown that the failure threshold of the LEA selected in this work under the rated condition is 27 mT and 14 mT in the positive and negative direction,*** a typical SMF of 10 mT in the negative direction,the closing time of the LEA will be extended by 40%,while its opening time will be shortened by about 10%.Experimental tests are also conducted,which verify the validity of the proposed model and the analysis *** paper provides a basis for the diamagnetic optimization design of LEA,and it is of great significance to ensure the reliable operation of the tokamak.

关键词： linear electromagnetic actuator stray magnetic field dynamic performance collision velocity

Microstructure Manipulation of Covalent Organic Frameworks(COFs)-based Membrane for Efficient Separations

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Chemical Research in Chinese Universities 2022年第2期38卷 325-338页

作者： MA Hanze wang shaoyu REN Yanxiong LIANG Xu wang Yuhan ZHU Ziting HE Guangwei JIANG Zhongyi Key Laboratory for Green Chemical Technology of Ministry of Education School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300350P.R.China Collaborative Innovation Center of Chemical Science and Engineering(Tianjin) Tianjin 300072P.R.China Joint School of National University of Singapore and Tianjin University International Campus of Tianjin UniversityFuzhou 350207P.R.China

Covalent organic framework(COF) membranes have exhibited great potential to become the next-generation membranes for efficient separations due to the diverse structures, ordered framework pores, tunable functionality and excellent stability. This review presents the microstructure manipulation strategies for separation performance enhancement of COF membranes in recent years. Based on the three mechanisms of molecular sieving, surface diffusion, and facilitated transport, the structural modulation methods to enhance the selectivity of COF membranes are analyzed in detail. Next, strategies of realizing ultrashort mass transfer pathways and ultralow mass transfer resistance for the permeability enhancement are elaborated. Furthermore, the framework stability in COFs, interlayer stability between COF nanosheets and interfacial stability between COF layer and substrate are discussed. Finally, we discuss the existing challenges and perspectives on the future development of COF membranes, targeting at identifying the most promising strategies and directions for the engineering of COF membranes.

关键词： Covalent organic framework Organic molecular sieve membrane Membrane separation Microporous material

Predictive Model of Live Shopping Interest Degree Based on Eye Movement Characteristics and Deep Factorization Machine

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Journal of Donghua University(English Edition) 2022年第4期39卷 353-360页

作者： SHI Xiujin LI Hao SHI Hang wang shaoyu SUN Guohao School of Computer Science and Technology Donghua UniversityShanghai 201620China

In the live broadcast process,eye movement characteristics can reflect people’s attention to the ***,the existing interest degree predictive model research does not consider the eye movement *** order to obtain the users’interest in the product more effectively,we will consider the key eye movement *** first collect eye movement characteristics based on the self-developed data processing algorithm fast discriminative model prediction for tracking(FDIMP),and then we add data dimensions to the original data set through information *** addition,we apply the deep factorization machine(DeepFM)architecture to simultaneously learn the combination of low-level and high-level *** order to effectively learn important features and emphasize relatively important features,the multi-head attention mechanism is applied in the interest *** experimental results on the public data set Criteo show that,compared with the original DeepFM algorithm,the area under curve(AUC)value was improved by up to 9.32%.

关键词： eye movement interest degree predictive deep factorization machine(DeepFM) multi-head attention mechanism

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Narrow Pooling Clothing Classification Based on Attention Mechanism

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Journal of Donghua University(English Edition) 2022年第4期39卷 367-372页

作者： MA Xiao wang shaoyu YE Shaoping FAN Jingyi XU An XIA Xiaoling School of Computer Science and Technology Donghua UniversityShanghai 201620China

In recent years,with the rapid development of e-commerce,people need to classify the wide variety and a large number of clothing images appearing on e-commerce *** order to solve the problems of long time consumption and unsatisfactory classification accuracy arising from the classification of a large number of clothing images,researchers have begun to exploit deep learning techniques instead of traditional learning *** paper explores the use of convolutional neural networks(CNNs)for feature learning to enhance global feature information interactions by adding an improved hybrid attention mechanism(HAM)that fully utilizes feature weights in three dimensions:channel,height,and ***,the improved pooling layer not only captures local feature information,but also fuses global and local information to improve the misclassification problem that occurs between similar *** on the Fashion-MNIST and DeepFashion datasets show that the proposed method significantly improves the accuracy of clothing classification(93.62%and 67.9%)compared with residual network(ResNet)and convolutional block attention module(CBAM).

关键词： clothing classification convolutional neural network(CNN) residual network(ResNet) attention mechanism narrow pooling

Residual Network with Enhanced Positional Attention and Global Prior for Clothing Parsing

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Journal of Donghua University(English Edition) 2022年第5期39卷 505-510页

作者： wang shaoyu HU Yun ZHU Yian YE Shaoping QIN Yanxia SHI Xiujin School of Computer Science and Technology Donghua UniversityShanghai 201620China

Clothing parsing, also known as clothing image segmentation, is the problem of assigning a clothing category label to each pixel in clothing images. To address the lack of positional and global prior in existing clothing parsing algorithms, this paper proposes an enhanced positional attention module(EPAM) to collect positional information in the vertical direction of each pixel, and an efficient global prior module(GPM) to aggregate contextual information from different sub-regions. The EPAM and GPM based residual network(EG-ResNet) could effectively exploit the intrinsic features of clothing images while capturing information between different scales and sub-regions. Experimental results show that the proposed EG-ResNet achieves promising performance in clothing parsing of the colorful fashion parsing dataset(CFPD)(51.12% of mean Intersection over Union(mIoU) and 92.79% of pixel-wise accuracy(PA)) compared with other state-of-the-art methods.

关键词： clothing parsing convolutional neural network positional attention global prior

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灾害应急状态终止的随机决策与仿真

哈尔滨工业大学学报 2014年第4期46卷 13-19页

作者：黄星王绍玉哈尔滨工业大学管理学院哈尔滨150001 哈尔滨工业大学建筑学院哈尔滨150001

为确定灾害应急状态终止时间,通过对应急状态终止状态影响因素的分析,将应急状态分为应急紧张状态和应急稳定状态2种,针对各状态指标先期的统计数据,结合马尔科夫过程,寻找出应急状态进入稳态概率分布的最大时间N,然后运用最优停止理论... 详细信息

为确定灾害应急状态终止时间,通过对应急状态终止状态影响因素的分析,将应急状态分为应急紧张状态和应急稳定状态2种,针对各状态指标先期的统计数据,结合马尔科夫过程,寻找出应急状态进入稳态概率分布的最大时间N,然后运用最优停止理论在N中寻找出应急状态终止的最优时间,并建立应急状态终止的马氏链决策-最优停止理论模型.基于马氏链的灾害应急状态终止模型能较准确地对应急状态终止时间进行量化决策,且计算简便,易于计算机实现,具有较强的可操作性,所提出的模型为掌握应急所处状态和对应急状态终止时间进行决策提供了理论支持.

关键词：应急状态终止马氏链模型稳态分布最优停止状态概率

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供水系统地震风险评估及升级优化

哈尔滨工业大学学报 2013年第2期45卷 20-25页

作者：王绍玉金书淼哈尔滨工业大学管理学院哈尔滨150001 哈尔滨工业大学建筑学院哈尔滨150001

为了评估供水系统地震风险和确定关键供水管道,建立了系统震后供水率S、管道升级收益指数U和管道断裂影响指数B 3项评价指标,并运用基于蒙特卡洛仿真的地震作用下流体的图解迭代响应分析(GIRAFFE)方法对供水系统在地面峰值速度vG=50 cm/... 详细信息

为了评估供水系统地震风险和确定关键供水管道,建立了系统震后供水率S、管道升级收益指数U和管道断裂影响指数B 3项评价指标,并运用基于蒙特卡洛仿真的地震作用下流体的图解迭代响应分析(GIRAFFE)方法对供水系统在地面峰值速度vG=50 cm/s时进行了风险分析.仿真结果表明,S的分布特征与节点的用水需求分布关系密切,U能作为首要指标并通过一次运算来确定系统中的单个关键供水管道和最大收益管道组合,它是管道断裂影响指数和管道断裂程度共同作用的结果.由单个关键供水管道组成的升级组合并不是最佳的升级优化策略,升级最大收益管道组合能最大程度地提高系统震后供水绩效并降低地震风险.

关键词：供水系统地震风险评估管道升级管道断裂蒙特卡洛仿真关键供水管道最大收益管道组合