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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4315-4321页

作者： Zhang, Ziyan Jiang, Bo Tang, Jin Tang, Jinhui Luo, Bin Anhui University School of Computer Science and Technology Hefei230009 China Nanjing University of Science and Technology School of Computer Science and Technology Nanjing210094 China

Graph convolutional networks (GCNs) gain increasing attention on graph data learning tasks in recent years. However, in many applications, graph may come with an incomplete form where attributes of graph nodes are partially unknown/missing. Existing graph convolutions (GCs) are generally designed on complete graphs which cannot deal with attribute-incomplete graph data directly. To address this problem, in this article, we extend standard GC and develop an explicit Partial Graph Convolution (PaGC) for attribute-incomplete graph data. Our PaGC is derived based on the observation that the core neighborhood aggregator in GC operation can be equivalently viewed as an energy minimization model. Based on it, we can define a novel partial aggregation function and derive PaGC for incomplete graph data. Experiments demonstrate the effectiveness and efficiency of the proposed PaGCN. © 2020 IEEE.

关键词： Convolution

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A multilayer network diffusion-based model for reviewer recommendation

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Chinese Physics B 2024年第3期33卷 700-717页

作者：黄羿炜徐舒琪蔡世民吕琳媛 Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 611731China Yangtze Delta Region Institute (Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China Institute of Dataspace Hefei Comprehensive National Science CenterHefei 230088China Big Data Research Center University of Electronic Science and Technology of ChinaChengdu 611731China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China School of Cyber Science and Technology University of Science and Technology of ChinaHefei 230026China

With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy *** systems are powerful tools developed in computer science and information science to deal with this ***,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform *** this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual *** network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among *** results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking *** work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.

关键词： reviewer recommendation multilayer network network diffusion model recommender systems complex networks

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Face Anti-Spoofing with Unknown Attacks:A Comprehensive Feature Extraction and Representation Perspective

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Journal of computer science & technology 2024年第4期39卷 827-840页

作者： Li-Min Li Bin-Wu Wang Xu Wang Peng-Kun Wang Yu-Dong Zhang Yang Wang School of Software Engineering University of Science and Technology of ChinaHefei 230000China School of Data Science University of Science and Technology of ChinaHefei 23000China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215000China

Face anti-spoofing aims at detecting whether the input is a real photo of a user(living)or a fake(spoofing)*** new types of attacks keep emerging,the detection of unknown attacks,known as Zero-Shot Face Anti-Spoofing(ZSFA),has become increasingly important in both academia and *** ZSFA methods mainly focus on extracting discriminative features between spoofing and living ***,the nature of the spoofing faces is to trick anti-spoofing systems by mimicking the livings,therefore the deceptive features between the known attacks and the livings,which have been ignored by existing ZSFA methods,are essential to comprehensively represent the ***,existing ZSFA models are incapable of learning the complete representations of living faces and thus fall short of effectively detecting newly emerged *** tackle this problem,we propose an innovative method that effectively captures both the deceptive and discriminative features distinguishing between genuine and spoofing *** method consists of two main components:a two-against-all training strategy and a semantic *** two-against-all training strategy is employed to separate deceptive and discriminative *** address the subsequent invalidation issue of categorical functions and the dominance disequilibrium issue among different dimensions of features after importing deceptive features,we introduce a modified semantic *** autoencoder is designed to map all extracted features to a semantic space,thereby achieving a balance in the dominance of each feature *** combine our method with the feature extraction model ResNet50,and experimental results show that the trained ResNet50 model simultaneously achieves a feasible detection of unknown attacks and comparably accurate detection of known *** results confirm the superiority and effectiveness of our proposed method in identifying the living with the interference of both known

关键词： face anti-spoofing spoof detection zero-shot learning convolutional neural network deep learning

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Porous FeP/FeO Deposited on Carbon Cloth with Accelerated Kinetics for the Hydrogen Evolution Reaction

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Journal of Wuhan university of technology(Materials science) 2024年第6期39卷 1434-1439页

作者： YU Hai ZHAO Yujia LIU Su ZUO Lei LEI Qianqian HU Ruiling LU Jianguo ZHAO Min WANG Congrong WANG Cunyong ZHANG Miao YANG Lei ZHONG Jin CAO Chunbin School of Physics and Materials Engineering and Key Laboratory for Photoelectric Detection Science and Technology of Education Department of Anhui Province Hefei Normal UniversityHefei 230601China School of Physics and Material Science Anhui UniversityHefei 230039China Department of Chemistry and Materials Engineering Hefei UniversityHefei 230601China School of Computer Science and Technology Hefei Normal UniversityHefei 230601China School of Science Anhui Agricultural UniversityHefei 230036China

FeP/FeO was prepared on carbon cloth(CC)via hydrothermal method,heat treatment in air,and phosphorization in ***/FeO/CC presents a porous and loose morphology which is conducive to the exposure of active sites and the transfer of ***/FeO/CC requires the low overpotentials of 257 and 117 mV(*** hydrogen electrode(RHE))to achieve the current density of 10 mA_·cm^(-2)for oxygen evolution reaction(OER)and hydrogen evolution reaction(HER)in alkaline KOH solution,*** small Tafel slope values of 36.1 mV_·dec^(-1)(for OER)and 96.2 mV_·dec^(-1)(for HER)indicate that FeP/FeO/CC exhibits the fast electrocatalytic reactive kinetics for OER and *** particular,the reaction kinetics of FeP/FeO/CC accelerated with the progress of *** charge-transfer resistance(R_(ct))of FeP/FeO/CC is only 11Ω.Excellent bifunctional electrocatalytic performances of FeP/FeO/CC should be attributed to the porous morphology and the lower charge-transfer resistance.

关键词： FeP/FeO/CC OER HER water splitting

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Long-term spatiotemporal variations of ammonia in the Yangtze River Delta region of china and its driving factors

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Journal of Environmental sciences 2025年第4期150卷 202-217页

作者： Jingkai Xue Chengzhi Xing Qihua Li Shanshan Wang Qihou Hu Yizhi Zhu Ting Liu Chengxin Zhang Cheng Liu School of Environmental Science and Optoelectronic Technology University of Science and Technology of ChinaHefei 230026China Key Lab of Environmental Optics&Technology Anhui Institute of Optics and Fine MechanicsHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Department of Precision Machinery and Precision Instrumentation University of Science and Technology of ChinaHefei 230026China Anhui Institute of Optics and Fine Mechanics Hefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes University of Science and Technology of ChinaHefei 230026China Institute of Physical Science and Information Technology Anhui UniversityHefei 230601China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention(LAP3) Department of Environmental Science and EngineeringFudan UniversityShanghai 200438China School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026China School of Environmental Science and Engineering Suzhou University of Science and TechnologySuzhou 215009China

This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in china’s Yangtze River Delta region(YRD)from 2008 to *** data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and *** spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural ***_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to *** highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to *** emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban *** within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)*** rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem *** concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)*** emphasizes the crucial role of environmental policies targeting the reduction of these acidic *** emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.

关键词： Yangtze River Delta Ammonia Spatiotemporal distribution Driving factors

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A Probabilistic Framework for Temporal Cognitive Diagnosis in Online Learning Systems

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Journal of computer science & technology 2023年第6期38卷 1203-1222页

作者：刘嘉聿汪飞马海平黄振亚刘淇陈恩红苏喻 School of Data Science University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Cognitive Intelligence Hefei 230088China Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of China Hefei 230026China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China School of Computer Science and Artificial Intelligence Hefei Normal UniversityHefei 230061China

Cognitive diagnosis is an important issue of intelligent education systems,which aims to estimate students'proficiency on specific knowledge *** existing studies rely on the assumption of static student states and ig-nore the dynamics of proficiency in the learning process,which makes them unsuitable for online learning *** this paper,we propose a unified temporal item response theory(UTIRT)framework,incorporating temporality and random-ness of proficiency evolving to get both accurate and interpretable diagnosis ***,we hypothesize that stu-dents'proficiency varies as a Wiener process and describe a probabilistic graphical model in UTIRT to consider temporali-ty and randomness ***,based on the relationship between student states and exercising answers,we hy-pothesize that the answering result at time k contributes most to inferring a student's proficiency at time k,which also re-flects the temporality aspect and enables us to get analytical maximization(M-step)in the expectation maximization(EM)algorithm when estimating model *** UTIRT is a framework containing unified training and inferenc-ing methods,and is general to cover several typical traditional models such as Item Response Theory(IRT),multidimen-sional IRT(MIRT),and temporal IRT(TIRT).Extensive experimental results on real-world datasets show the effective-ness of UTIRT and prove its superiority in leveraging temporality theoretically and practically over TIRT.

关键词： cognitive diagnosis probabilistic graphical model item response theory(IRT) stochastic process expectation maximization(EM)algorithm

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Electronic thermal conductivity of tungsten-based systems during collision cascade processes

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Nuclear science and Techniques 2025年第5期36卷 167-176页

作者： Jiong-Rong Wang Bi-Cai Pan Key Laboratory of Strongly-Coupled Quantum Matter Physics Department of PhysicsUniversity of Science and Technology of ChinaHefei 230026China Hefei National Laboratory for Physical Sciences at Microscale University of Science and Technology of ChinaHefei 230026China

The thermal conductivity of plasma-facing materials(PFM)exposed to intense radiation is a critical concern for the reliable usage of materials in fusion ***,limited research has been performed regarding the thermal conductivity of structures that rapidly change in a short time during collision cascade processes under *** this study,we employed the tight-binding(TB)method to investigate the electronic thermal conductivity(κ_(e))of tungsten-based systems during various cascading *** found thatκ_(e) values sharply decrease within the initial 0.3 picoseconds and then partially recover at a slow pace;this is closely linked to the evolution of defects and microstructural *** increase in the initial kinetic energy of the primary knock-on atom and the presence of a high concentration of hydrogen atoms further decrease theκ_(e) ***,higher temperatures have a significant positive effect onκ_(e).Furthermore,the presence of a grain boundary∑5[001](130)substantially reducesκ_(e),whereas the absorption effect of point defects by the grain boundary has little influence onκ_(e) during *** findings provide a theoretical basis for evaluating changes in the thermal conductivity performance of PFMs during their usage in nuclear fusion reactors.

关键词： Electronic thermal conductivity Collision cascade Tungsten Plasma-facing materials Tight-binding calculations

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Interplay between the atomic structures and superconductivity of two-monolayer Pb films

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science china(Physics,Mechanics & Astronomy) 2024年第1期67卷 90-98页

作者： Kun Xie Ze Huang Pengju Li Yumin Xia Desheng Cai Yitong Gu Yuzhou Liu Fangliang Cai Runxiao Zhang Haohao Shi Ping Cui Shengyong Qin International Center for Quantum Design of Functional Materials(ICQD) University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory of Strongly Coupled Quantum Matter Physics Department of PhysicsUniversity of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China

Superconductors with reduced dimensionality have been widely explored for their exotic superconducting ***,at the two-dimensional limit,two-monolayer Pb films with two types of structures provide an ideal platform to unveil the underlying superconducting mechanism[science 324,1314(2009)].Here,by combining scanning tunneling microscopy(STM)with the first-principle calculations,we successfully identify that these two types have different atomic lattice structures with varying stacking phases,which further enables us to calculate the phonon spectrum and electron phonon coupling strength of each *** theoretical calculations are in good agreement with tunneling spectroscopy measurements of the superconducting transition temperatures(T_(c)),which established a correlation between atomic structures and ***,it was observed that the higher T_(c)of these two types also possess higher out-of-plane upper critical magnetic fields(Hc2).These findings will provide important new insights into two-dimensional superconductivity at the atomic level.

关键词： 2 ML Pb films superconductivity atomic structure scanning tunneling microscopy first-principle calculations

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A recover-then-discriminate framework for robust anomaly detection

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science china(Information sciences) 2025年第4期68卷 300-318页

作者： Peng XING Dong ZHANG Jinhui TANG Zechao LI School of Computer Science and Engineering Nanjing University of Science and Technology Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology

Anomaly detection(AD) has been extensively studied and applied across various scenarios in recent years. However, gaps remain between the current performance and the desired recognition accuracy required for practical *** paper analyzes two fundamental failure cases in the baseline AD model and identifies key reasons that limit the recognition accuracy of existing approaches. Specifically, by Case-1, we found that the main reason detrimental to current AD methods is that the inputs to the recovery model contain a large number of detailed features to be recovered, which leads to the normal/abnormal area has not/has been recovered into its original state. By Case-2, we surprisingly found that the abnormal area that cannot be recognized in image-level representations can be easily recognized in the feature-level representation. Based on the above observations, we propose a novel recover-then-discriminate(ReDi) framework for *** takes a self-generated feature map(e.g., histogram of oriented gradients) and a selected prompted image as explicit input information to address the identified in Case-1. Additionally, a feature-level discriminative network is introduced to amplify abnormal differences between the recovered and input representations. Extensive experiments on two widely used yet challenging AD datasets demonstrate that ReDi achieves state-of-the-art recognition accuracy.

关键词： recovery network HOG prompt discriminative network self-correlation loss anomaly detection

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A Trusted Medical Image Zero-watermarking Scheme Based On DCNN and Hyperchaotic System

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IEEE Journal of Biomedical and Health Informatics 2025年第6期29卷 4241-4253页

作者： Xiang, Ruotong Liu, Gang Dang, Min Wangn, Quan Pan, Rong Xidian University School of Computer Science & Technology China Xidian University Department of Computer Science & Technology China

The zero-watermarking methods provide a means of lossless, which was adopted to protect medical image copyright requiring high integrity. However, most existing studies have only focused on robustness and there has been little discussion about the analysis and experiment on discriminability. Therefore, this paper proposes a trusted robust zero-watermarking scheme for medical images based on Deep convolution neural network (DCNN) and the hyperchaotic encryption system. Firstly, the medical image is converted into several feature map matrices by the specific convolution layer of DCNN. Then, a stable Gram matrix is obtained by calculating the colinear correlation between different channels in feature map matrices. Finally, the Gram matrixes of the medical image and the feature map matrixes of the watermark image are fused by the trained DCNN to generate the zero-watermark. Meanwhile, we propose two feature evaluation criteria for finding differentiated eigenvalues. The eigenvalue is used as the explicit key to encrypt the generated zero-watermark by Lorenz hyperchaotic encryption, which enhances security and discriminability. The experimental results show that the proposed scheme can resist common image attacks and geometric attacks, and is distinguishable in experiments, being applicable for the copyright protection of medical images. © 2013 IEEE.

关键词： Eigenvalues and eigenfunctions

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