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Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

CAAI Transactions on Intelligence Technology 2024年第3期9卷 769-786页

作者： Xiaojun Pu Jiaqi Zhu Yunkun Wu Chang Leng Zitong Bo Hongan Wang Institute of software Chinese Academy of Sciences BeijingChina Ecovacs Robotics Co. Ltd.SuzhouJiangsuChina Automotive software Innovation center ChongqingChina

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 ***,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal ***,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction *** DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency *** dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained ***,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained *** performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute *** results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of *** spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various *** conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.

关键词： adaptive COVID-19 forecasting dynamic intervention spatio-temporal graph neural networks

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ASTSDL:predicting the functionality of incomplete programming code via an AST-sequence-based deep learning model

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Science China(Information Sciences) 2024年第1期67卷 86-104页

作者： Yaoshen YU Zhiqiu HUANG Guohua SHEN Weiwei LI Yichao SHAO College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Collaborative Innovation center of Novel software Technology and Industrialization Key Laboratory of Safety-Critical software Ministry of Industry and Information Technology

Code recommendation systems have been widely used in helping developers implement unfamiliar programming *** existing code recommenders or code search engines can retrieve relevant code rapidly with high accuracy,however,they cannot recommend any code outside similar *** propose an approach to predict the functionality of incomplete programming code by using syntactical information,and providing a list of potential functionalities to guess what the developers want,in order to increase the diversity of *** this paper,we propose a deep learning model called ASTSDL,which uses a sequencebased representation of source code to predict *** extract syntactical information from the abstract syntax tree(AST) of the source code,apply a deep learning model to capture the syntactic and sequential information,and predict the functionality of the source code *** experimental results demonstrate that ASTSDL can effectively predict the functionality of incomplete code with an accuracy above 84% in the top-10 list,even if there is only half of the complete code.

关键词： functionality prediction incomplete programming code syntactical information code representation model deep learning algorithm

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Blockchain Meets Generative Behavior Steganography:A Novel Covert Communication Framework for Secure IoT Edge Computing

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Chinese Journal of Electronics 2024年第4期33卷 886-898页

作者： Yuanlong CAO Junjie LI Kailin CHAO Jianmao XIAO Gang LEI School of Computer Information Engineering Jiangxi Normal University Jiangxi Blockchain Data Security and Governance Engineering research center Jiangxi Normal University School of software Jiangxi Normal University

The rapid development of Internet of things(Io T) and edge computing technologies has brought forth numerous possibilities for the intelligent and digital future. The frequent communication and interaction between devices inevitably generate a large amount of sensitive information. Deploying a blockchain network to store sensitive data is crucial for ensuring privacy and security. The openness and synchronicity of blockchain networks give rise to challenges such as transaction privacy and storage capacity issues, significantly impeding their development in the context of edge computing and Io T. This paper proposes a reliable fog computing service solution based on a blockchain fog architecture. This paper stores data files in the inter planetary file system(IPFS) and encrypts the file hash values used for retrieving data files with stream cipher encryption. It employs a steganographic transmission technique leveraging Alpha Zero's Gomoku algorithm to discretely transmit the stream cipher key across the blockchain network without a carrier, thus achieving dual encryption. This approach aims to mitigate the storage burden on the blockchain network while ensuring the security of transaction data. Experimental results demonstrate that the model enhances the transmission capacity of confidential information from kilobytes(KB) to megabytes(MB) and exhibits high levels of covert and security features.

关键词： Steganography Ciphers Privacy Data privacy Blockchains Encryption Internet of Things

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Polyzwitterionic cross-linked double network hydrogel electrolyte enabling high-stable Zn anode

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Nano research 2024年第6期17卷 5278-5287页

作者： Mengyu Shi Junlong Zhang Guochuan Tang Ben Wang Sen Wang Xiaoxian Ren Guojie Li Weihua Chen Chuntai Liu Changyu Shen State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China College of Chemistry and Green Catalysis center Zhengzhou UniversityZhengzhou 450001China research Institute of Interdisciplinary Science and School of Materials Science and Engineering Dongguan University of TechnologyDongguan 523808China

Zn metal anode suffers from dendrite issues and passive byproducts,which severely plagues the practical application of aqueous Zn metal ***,a polyzwitterionic cross-linked double network hydrogel electrolyte composed of physical crosslinking(hyaluronic acid)and chemical crosslinking(synthetic zwitterionic monomer copolymerized with acrylamide)is introduced to overcome these *** the one hand,highly hydrophilic physical network provides an energy dissipation channel to buffer stress and builds a H_(2)O-poor interface to avoid side *** the other hand,the charged groups(sulfonic and imidazolyl)in chemical crosslinking structure build anion/cation transport channels to boost ions’kinetics migration and regulate the typical solvent structure[Zn(H_(2)O)_(6)]^(2+)to R-SO_(3)^(−)[Zn(H_(2)O)_(4)]^(2+),with uniform electric field distribution and significant resistance to dendrites and parasitic *** on the above functions,the symmetric zinc cell exhibits superior cycle stability for more than 420 h at a high current density of 5 mA·cm^(−2),and Zn||MnO_(2)full cell has a reversible specific capacity of 150 mAh·g^(−1)after 1000 cycles at 2 C with this hydrogel ***,the pouch cell delivers impressive flexibility and cyclability for energy-storage applications.

关键词： Zn anode dendrites parasitic reactions polyzwitterion double network hydrogel electrolyte

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software Defect Prediction Method Based on Stable Learning

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Computers, Materials & Continua 2024年第1期78卷 65-84页

作者： Xin Fan Jingen Mao Liangjue Lian Li Yu Wei Zheng Yun Ge College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing210012China School of software Nanchang Hangkong UniversityNanchang330029China software Testing and Evaluation center Nanchang Hangkong UniversityNanchang330029China

The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and *** previous software defect prediction studies,transfer learning was effective in solving the problem of inconsistent project data ***,target projects often lack sufficient data,which affects the performance of the transfer learning *** addition,the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning *** address these problems,this article propose a software defect prediction method based on stable learning(SDP-SL)that combines code visualization techniques and residual *** method first transforms code files into code images using code visualization techniques and then constructs a defect prediction model based on these code *** the model training process,target project data are not required as prior *** the principles of stable learning,this paper dynamically adjusted the weights of source project samples to eliminate dependencies between features,thereby capturing the“invariance mechanism”within the *** approach explores the genuine relationship between code defect features and labels,thereby enhancing defect prediction *** evaluate the performance of SDP-SL,this article conducted comparative experiments on 10 open-source projects in the PROMISE *** experimental results demonstrated that in terms of the F-measure,the proposed SDP-SL method outperformed other within-project defect prediction methods by 2.11%-44.03%.In cross-project defect prediction,the SDP-SL method provided an improvement of 5.89%-25.46% in prediction performance compared to other cross-project defect prediction ***,SDP-SL can effectively enhance within-and cross-project defect predictions.

关键词： software defect prediction code visualization stable learning sample reweight residual network

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Leader-Following Consensus of Multi-Agent Systems via Fully Distributed Event-Based Control

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 640-645页

作者： GENG Zongsheng ZHAO Dongdong ZHOU Xingwen YAN Lei YAN Shi School of Information Science and Engineering Lanzhou UniversityLanzhou730000China Engineering research center of Open-Source software and Real-Time Systems of Ministry of Education Lanzhou UniversityLanzhou730000China

This paper aims to study the leader-following consensus of linear multi-agent systems on undirected ***,we construct an adaptive event-based protocol that can be implemented in a fully distributed way by using only local relative *** protocol is also resource-friendly as it will be updated only when the agent violates the designed event-triggering function.A sufficient condition is proposed for the leader-following consensus of linear multi-agent systems based on the Lyapunov approach,and the Zeno-behavior is ***,two numerical examples are provided to illustrate the effectiveness of the theoretical results.

关键词： consensus multi-agent systems event-based control adaptive control fully distributed protocol

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Highly oriented MXene/polyvinyl alcohol films prepared by scalable layer-by-layer blade coating for efficient electromagnetic interference shielding and infrared stealth

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Nano research 2024年第6期17卷 5651-5660页

作者： Jingyu Dong Zhaoyang Li Congqi Liu Bing Zhou Chuntai Liu uezhan Feng State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China Shangqiu Normal University Shangqiu 476000China

Controlling the orientation of two-dimensional MXene within layered films is essential to optimize or tune their mechanical properties and electromagnetic interference shielding(EMI)performance,but achieving the high orientation MXene layers on an industrial scale remains a challenging *** this paper,a scalable layer-by-layer blade coating(LbLBC)method was employed to fabricate highly oriented MXene/polyvinyl alcohol(PVA)*** the LbLBC process,MXene/PVA colloid suffered a strong shearing effect,which induced the ordered alignment of MXene nanosheets along the direction of the blade *** orientation of MXene can be effectively adjusted by changing the scraping gap of LbLBC,achieving a maximum Herman orientation factor f of *** a result,the mechanical properties and EMI performance of the as-prepared MXene/PVA films are in direct proportion to their orientation,with the optimal values of tensile strength of 145.5 MPa,fracture strain of 19.6%,toughness of 17.7 MJ·m^(−3),and EMI shielding effectiveness of 36.7 ***,the inherently low mid-infrared(mid-IR)emissivity of MXene,combined with the densely oriented structure affords the composite films with IR stealth,resulting in a substantial decrease from 150 to 66.1℃in the radiative temperature of a ***,these scalable MXene/PVA films exhibit remarkable potential for integration into the next generation of multifunctional protective camouflage materials.

关键词： MXene nanosheets densely oriented structure layer-by-layer blade coating electromagnetic interference shielding infrared stealth

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Analysis of the acoustoelectric response of SAW gas sensors using a COM model

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Microsystems & Nanoengineering 2024年第3期10卷 87-96页

作者： Yang Yuan Tao Yang Xi Chen Linglang Yu Xiaoxiao Hou Guangzu Zhang Wen Dong Zixiao Lu Honglang Li Leonhard Reindl Wei Luo School of Integrated Circuits Huazhong University of Science and Technology430074 WuhanPeople’s Republic of China CAS center for Excellence in Nanoscience National Center for Nanoscience and Technology100190 BeijingPeople’s Republic of China Department of Microsystems Engineering Laboratory for Electrical Instrumentation and Embedded SystemsUniversity of Freiburg79110 FreiburgGermany research Institute of Huazhong University of Science and Technology in Shenzhen 518057 ShenzhenPeople’s Republic of China

Surface acoustic wave(SAW)gas sensors based on the acoustoelectric effect exhibit wide application prospects for in situ gas ***,establishing accurate models for calculating the scattering parameters of SAW gas sensors remains a ***,we present a coupling of modes(COM)model that includes the acoustoelectric effect and specifically explains the nonmonotonic variation in the center frequency with respect to the sensing film’s sheet *** sensing parameters of the gas sensors,including the center frequency,insertion loss,and phase,were experimentally compared for accuracy and ***,the frequency of the phase extremum(FPE)shift was determined to vary monotonically,and the range of selectable test points was wide,making the FPE an appropriate response parameter for leveraging in SAW gas *** simulation results of the COM model were highly consistent with the experimental *** study is proposed to provide theoretical guidance for the future development of gas SAW sensors.

关键词： COM SAW establishing

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Meta-Auto-Decoder:a Meta-Learning-Based Reduced Order Model for Solving Parametric Partial Differential Equations

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Communications on Applied Mathematics and Computation 2024年第2期6卷 1096-1130页

作者： Zhanhong Ye Xiang Huang Hongsheng Liu Bin Dong Beijing International center for Mathematical research Peking UniversityBeijing 100871China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230027AnhuiChina Central software Institute Huawei Technologies Co.LtdHangzhou 310007ZhejiangChina center for Machine Learning research Peking UniversityBeijing 100871China

Many important problems in science and engineering require solving the so-called parametric partial differential equations(PDEs),i.e.,PDEs with different physical parameters,boundary conditions,shapes of computational domains,*** reduced order modeling techniques accelerate the solution of the parametric PDEs by projecting them onto a linear trial manifold constructed in the ofline *** methods often need a predefined mesh as well as a series of precomputed solution snapshots,and may struggle to balance between the efficiency and accuracy due to the limitation of the linear *** the nonlinear representation of neural networks(NNs),we propose the Meta-Auto-Decoder(MAD)to construct a nonlinear trial manifold,whose best possible performance is measured theoretically by the decoder *** on the meta-learning concept,the trial manifold can be learned in a mesh-free and unsupervised way during the pre-training *** adaptation to new(possibly heterogeneous)PDE parameters is enabled by searching on this trial manifold,and optionally fine-tuning the trial manifold at the same *** numerical experiments show that the MAD method exhibits a faster convergence speed without losing the accuracy than other deep learning-based methods.

关键词： Parametric partial differential equations(PDEs) Meta-learning Reduced order modeling Neural networks(NNs) Auto-decoder

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Deep learning based water leakage detection for shield tunnel lining

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 887-898页

作者： Shichang LIU Xu XU Gwanggil JEON Junxin CHEN Ben-Guo HE College of Computer Science Sichuan UniversityChengdu 610065China School of Computer Science and Engineering Northeastern UniversityShenyang 110004China Department of embedded Systems Engineering Incheon National UniversityIncheon 22012Korea School of software Dalian University of TechnologyDalian 116621China Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines Northeastern UniversityShenyang 110819China

Shield tunnel lining is prone to water leakage,which may further bring about corrosion and structural damage to the walls,potentially leading to dangerous *** avoid tedious and inefficient manual inspection,many projects use artificial intelligence(Al)to detect cracks and water leakage.A novel method for water leakage inspection in shield tunnel lining that utilizes deep learning is introduced in this *** proposal includes a ConvNeXt-S backbone,deconvolutional-feature pyramid network(D-FPN),spatial attention module(SPAM).and a detection *** can extract representative features of leaking areas to aid inspection *** further improve the model's robustness,we innovatively use an inversed low-light enhancement method to convert normally illuminated images to low light ones and introduce them into the training *** experiments are performed,achieving the average precision(AP)score of 56.8%,which outperforms previous work by a margin of 5.7%.Visualization illustrations also support our method's practical effectiveness.

关键词： water leakage detection deep learning deconvolutional-feature pyramid spatial attention

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