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Recommendation System Based on Perceptron and Graph Convolution Network

Computers, Materials & Continua 2024年第6期79卷 3939-3954页

作者： zuozheng lian Yongchao Yin Haizhen Wang College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar161006China

The relationship between users and items,which cannot be recovered by traditional techniques,can be extracted by the recommendation algorithm based on the graph convolution *** current simple linear combination of these algorithms may not be sufficient to extract the complex structure of user interaction *** paper presents a new approach to address such issues,utilizing the graph convolution network to extract association *** proposed approach mainly includes three modules:Embedding layer,forward propagation layer,and score prediction *** embedding layer models users and items according to their interaction information and generates initial feature vectors as input for the forward propagation *** forward propagation layer designs two parallel graph convolution networks with self-connections,which extract higher-order association relevance from users and items separately by multi-layer graph ***,the forward propagation layer integrates the attention factor to assign different weights among the hop neighbors of the graph convolution network fusion,capturing more comprehensive association relevance between users and items as input for the score prediction *** score prediction layer introduces MLP(multi-layer perceptron)to conduct non-linear feature interaction between users and items,***,the prediction score of users to items is *** recall rate and normalized discounted cumulative gain were used as evaluation *** proposed approach effectively integrates higher-order information in user entries,and experimental analysis demonstrates its superiority over the existing algorithms.

关键词： Recommendation system graph convolution network attention mechanism multi-layer perceptron

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Maximizing Influence in Temporal Social Networks:A Node Feature-Aware Voting Algorithm

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Computers, Materials & Continua 2023年第12期77卷 3095-3117页

作者： Wenlong Zhu Yu Miao Shuangshuang Yang zuozheng lian lianhe Cui College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar161006China College of Teacher Education Qiqihar UniversityQiqihar161006China

Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of ***,most existing studies on the IM problem focus on static social network features,while neglecting the features of temporal social *** bridge this gap,we focus on node features reflected by their historical interaction behavior in temporal social networks,i.e.,interaction attributes and self-similarity,and incorporate them into the influence maximization algorithm and information propagation ***,we propose a node feature-aware voting algorithm,called ISVoteRank,for seed nodes ***,before voting,the algorithm sets the initial voting ability of nodes in a personalized manner by combining their *** the voting process,voting weights are set based on the interaction strength between nodes,allowing nodes to vote at different extents and subsequently weakening their voting ability *** process concludes by selecting the top k nodes with the highest voting scores as seeds,avoiding the inefficiency of iterative seed selection in traditional voting-based ***,we extend the Independent Cascade(IC)model and propose the Dynamic Independent Cascade(DIC)model,which aims to capture the dynamic features in the information propagation process by combining node ***,experiments demonstrate that the ISVoteRank algorithm has been improved in both effectiveness and efficiency compared to baseline methods,and the influence spread through the DIC model is improved compared to the IC model.

关键词： Temporal social networks influence maximization voting strategy interactive properties self-similarity

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An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

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Computers, Materials & Continua 2023年第5期75卷 3111-3131页

作者： Wenlong Zhu Yu Miao Shuangshuang Yang zuozheng lian lianhe Cui College of Computer and Control Engineering of Qiqihar University Qiqihar161006China College of Teacher Education of Qiqihar University Qiqihar161006China

Influence maximization of temporal social networks(IMT)is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely *** solve the IMT problem,we propose an influence maximization algorithm based on an improved K-shell method,namely improved K-shell in temporal social networks(KT).The algorithm takes into account the global and local structures of temporal social ***,to obtain the kernel value Ks of each node,in the global scope,it layers the network according to the temporal characteristic of nodes by improving the K-shell ***,in the local scope,the calculation method of comprehensive degree is proposed to weigh the influence of ***,the node with the highest comprehensive degree in each core layer is selected as the ***,the seed selection strategy of KT can easily lose some influential ***,by optimizing the seed selection strategy,this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization(KTIM).According to the hierarchical distribution of cores,the algorithm adds nodes near the central core to the candidate seed *** then searches for seeds in the candidate seed set according to the comprehensive *** showthatKTIMis close to the best performing improved method for influence maximization of temporal graph(IMIT)algorithm in terms of effectiveness,but runs at least an order of magnitude faster than ***,considering the effectiveness and efficiency simultaneously in temporal social networks,the KTIM algorithm works better than other baseline algorithms.

关键词： Temporal social network influence maximization improved K-shell comprehensive degree

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Enhancement of Biomass Material Characterization Images Using an Improved U-Net

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Computers, Materials & Continua 2022年第7期72卷 1515-1528页

作者： zuozheng lian Hong Zhao Qianjun Zhang Haizhen Wang E.Erdun College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China College of Light Industry and Textile Qiqihar UniversityQiqihar161006China Elastic Block Store Performance Team Amazon Web ServicesBoston02210USA

For scanning electronmicroscopes with high resolution and a strong electric field,biomass materials under observation are prone to radiation damage from the electron *** results in blurred or non-viable images,which affect further observation of material microscopic morphology and *** blurred images to their original sharpness is still a challenging problem in image *** can’t effectively separate image context dependency and texture information,affect the effect of image enhancement and deblurring,and are prone to gradient disappearance during model training,resulting in great difficulty in model *** this paper,we propose the use of an improvedU-Net(U-shapedConvolutional Neural Network)to achieve image enhancement for biomass material characterization and restore blurred images to their original *** main work is as follows:use of depthwise separable convolution instead of standard convolution in U-Net to reduce model computation effort and parameters;embedding wavelet transform into the U-Net structure to separate image context and texture information,thereby improving image reconstruction quality;using dense multi-receptive field channel modules to extract image detail information,thereby better transmitting the image features and network gradients,and reduce the difficulty of *** experiments show that the improved U-Net model proposed in this paper is suitable and effective for enhanced deblurring of biomass material characterization *** PSNR(Peak Signal-to-noise Ratio)and SSIM(Structural Similarity)are enhanced as well.

关键词： U-Net wavelet transform image enhancement biomass material characterization

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Revisiting thermal comfort and thermal sensation

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Building Simulation 2024年第2期17卷 185-188页

作者： Zhiwei lian Department of Architecture Shanghai Jiao Tong UniversityShanghai200240China

The thermal environment is closely intertwined with comfort,health,efficiency,and building energy *** Comfort stands as a crucial concept for evaluating the thermal environment,yet the prevailing evaluation metric is Thermal *** correspondence between genuine Thermal Comfort and Thermal Sensation is influenced by a variety of environmental factors.

关键词： thermal Comfort prevailing

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Modeling and Simulation of Lithium Vacuum Evaporation Process Using COMSOL Multiphysics

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Journal of Thermal Science 2024年第1期33卷 86-100页

作者： lian Xuexin ZHONG Dawen Beijing Key Laboratory of Passive Nuclear Power Safety and Technology North China Electric Power UniversityBeijing 102206China

Based on the COMSOL Multiphysics simulation software,this study carried out modeling and numerical simulation for the evaporation process of liquid metal lithium in the vacuum free molecular flow *** motion of lithium atoms in the evaporation process was analyzed through a succession of *** on the available experimental values of the saturated vapor pressure of liquid metal lithium,the relationship between saturated vapor pressure and temperature of liquid lithium in the range of 600 K-900 K was obtained.A two-dimensional symmetric model(3.5 mm×20 mm) was established to simulate the transient evaporation process of liquid lithium at wall temperatures of 750 K,780 K,800 K,810 K,825 K,and 850 K,*** effects of temperature,the evaporation coefficient,back pressure,and length-to-diameter ratio on the evaporation process were studied;the variation trends and reasons of the molecular flux and the pressure during the evaporation process were *** the same time,the evaporation process under variable wall temperature conditions was *** research made the evaporation process of liquid lithium in vacuum molecular flow clearer,and provided theoretical support for the space reactor and nuclear fusion related fields.

关键词： free molecular flow saturated vapor pressure vacuum evaporation liquid lithium metal

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DeepSI:A Sensitive-Driven Testing Samples Generation Method of Whitebox CNN Model for Edge Computing

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Tsinghua Science and Technology 2024年第3期29卷 784-794页

作者： Zhichao lian Fengjun Tian School of Cyber Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China

In recent years,Deep Learning(DL)technique has been widely used in Internet of Things(IoT)and Industrial Internet of Things(IIoT)for edge computing,and achieved good *** more and more studies have shown the vulnerability of neural ***,it is important to test the robustness and vulnerability of neural *** specifically,inspired by layer-wise relevance propagation and neural network verification,we propose a novel measurement of sensitive neurons and important neurons,and propose a novel neuron coverage criterion for robustness *** on the novel criterion,we design a novel testing sample generation method,named DeepSI,which involves definitions of sensitive neurons and important ***,we construct sensitive-decision paths of the neural network through selecting sensitive neurons and important ***,we verify our idea by setting up several experiments,then results show our proposed method achieves superior performances.

关键词： neuron sensitivity Layer-wise Relevance Propagation(LRP) neural network verification deeplearning testing

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Contrasting physical mechanisms of yellowfin tuna fluctuations between the western and eastern Indian Ocean

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Journal of Oceanology and Limnology 2024年第3期42卷 960-971页

作者： Peng lian Le GAO Key Laboratory of Ocean Observation and Forecasting and Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100049China Laboratory for Ocean Dynamics and Climate Laoshan LaboratoryQingdao 266061China

As an economically critical pelagic migratory species,yellowfin tuna(Thunnus albacores,YFT)is very sensible to physical and environmental conditions,such as sea surface temperature(SST),ocean heat content(OHC),and the mixed layer depth(MLD).We investigated the impact of SST,OHC,and MLD on fluctuations of YFT catch in the western/eastern Indian Ocean using the long time series of 63-year environmental and YFT *** found that the impact of SST on YFT was heavily overestimated in the past,and MLD plays a more critical role in the YFT catch *** the MLD deepens(>34.8 m),SST was more influential in predicting the catches of YFT than OHC in the western Indian Ocean,and OHC was more critical to YFT than SST in the eastern Indian ***,when the MLD shallows(<34.8 m),MLD was more vital to predict the catch per unit effort(CPUE)of YFT than SST/OHC in the *** 2000,there was an asynchronous pattern of YFT CPUE induced by higher frequency variations and ocean hiatus of SST/OHC signals in the western and eastern Indian Oceans *** impact of the subsurface hiatus may induce the decrease of YFT in the eastern Indian *** above findings clarified a non-stationary relationship between the environmental factors and catches of YFT and provided new insights into variations in YFT abundance.

关键词： yellowfin tuna Indian Ocean sea surface temperature(SST) ocean heat content(OHC) mixed layer depth(MLD) hiatus

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Impacts of central-Pacific El Niño and physical drivers on eastern Pacific bigeye tuna

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Journal of Oceanology and Limnology 2024年第3期42卷 972-987页

Bigeye tuna Thunnus obesus is an important migratory species that forages deeply,and El Niño events highly influence its distribution in the eastern Pacific *** sea surface temperature is widely recognized as the main factor affecting bigeye tuna(BET)distribution during El Niño events,the roles of different types of El Niño and subsurface oceanic signals,such as ocean heat content and mixed layer depth,remain *** conducted A spatial-temporal analysis to investigate the relationship among BET distribution,El Niño events,and the underlying oceanic signals to address this knowledge *** used monthly purse seine fisheries data of BET in the eastern tropical Pacific Ocean(ETPO)from 1994 to 2012 and extracted the central-Pacific El Niño(CPEN)indices based on Niño 3 and Niño ***,we employed Explainable Artificial Intelligence(XAI)models to identify the main patterns and feature importance of the six environmental variables and used information flow analysis to determine the causality between the selected factors and BET ***,we analyzed Argo datasets to calculate the vertical,horizontal,and zonal mean temperature differences during CPEN and normal years to clarify the oceanic thermodynamic structure differences between the two types of *** findings reveal that BET distribution during the CPEN years is mainly driven by advection feedback of subsurface warmer thermal signals and vertically warmer habitats in the CPEN domain area,especially in high-yield fishing *** high frequency of CPEN events will likely lead to the westward shift of fisheries centers.

关键词： bigeye tuna central-Pacific El Niño(CPEN) ocean heat content Argo explainable artificial intelligence(XAI) information flow

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Emerging materials and transistors for integrated circuits

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National Science Review 2024年第3期11卷 7-8页

作者： Ming Liu lian-Mao Peng Lab of Nanofabrication and Novel Device Integration Institute of Microelectronics Chinese Academy of Sciences Key Laboratory for the Physics and Chemistry of Nanodevices and Center for Carbon-based Electronics School of Electronics Peking University

The device technology for integrated circuits(ICs) has received a great deal of attention in the past decade since the mainstream silicon-based complementary metal-oxide-semiconductor(CMOS) field-effect transistor(FET) for modern ICs had been encountering development bottlenecks due to the combination of power constraints, physics, cost and fabrication processes.

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