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Acta Mathematica Sinica,English Series 2024年第7期40卷 1697-1726页

作者： Timilehin Opeyemi Alakoya Oluwatosin Temitope Mewomo school of Mathematics Statistics and Computer ScienceUniversity of KwaZulu-NatalDurbanSouth Africa

In this paper,we study the concept of split monotone variational inclusion problem with multiple output *** propose a new relaxed inertial iterative method with self-adaptive step sizes for approximating the solution of the problem in the framework of Hilbert *** proposed algorithm does not require the co-coerciveness nor the Lipschitz continuity of the associated single-valued ***,some parameters are relaxed to accommodate a larger range of values for the step *** some mild conditions on the control parameters and without prior knowledge of the operator norms,we obtain strong convergence result for the proposed ***,we apply our result to study certain classes of optimization problems and we present several numerical experiments to demonstrate the implementability of the proposed *** of the existing results in the literature could be viewed as special cases of our result in this paper.

关键词： Split inverse problems non-Lipschitz operators inertial technique self-adaptive step sizes

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What can we learn from quality assurance badges in open-source software?

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science China(Information sciences) 2024年第4期67卷 146-163页

作者： Feng LI Yiling LOU Xin TAN Zhenpeng CHEN Jinhao DONG Yang LI Xuanzhi WANG Dan HAO Lu ZHANG MoE Key Lab of HCST School of Computer SciencePeking University Department of computer science Purdue University school of computer science & Engineering Beihang University(BUAA) Department of computer science University College London(UCL)

In the development of open-source software(OSS), many developers use badges to give an overview of the software and share some key features/metrics conveniently. Among various badges, quality assurance(QA) badges make up a large proportion and are the most prevalent because QA is of vital importance in software development, and ineffective QA may lead to anomalies or defects. In this paper, we focus on QA badges in open-source projects, which present quality assurance information directly and instantly,and aim to produce some interesting findings and provide practical implications. We collect and analyze 100000 projects written in popular programming languages from GitHub and conduct a comprehensive empirical study both inside and outside QA badges. Inside QA badges, we build a category classification for all QA badges based on the properties they focus on, which shows the types of QA badges developers use. Then,we analyze the frequency of the properties that QA badges focus on, and property combinations, too, which present their use status. We find that QA badges focus on various properties while developers give different preferences to different properties. The use status also differs between different programming languages. For example, projects written in C focus on Security to a great extent. Our findings also provide implications for developers and badge providers. Outside QA badges, we conduct a correlation analysis between QA badges and some software metrics that have potential relationships with code quality, contribution quality, and popularity. We find that QA badges have statistically significant correlations with various software metrics.

关键词： quality assurance badge open-source software code quality empirical study

APF-GAN:Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network

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Computational Visual Media 2024年第1期10卷 187-192页

作者： Yuxuan Li Lingfeng Yang Xiang Li college of computer science Nankai UniversityTianjinChina school of computer science and Engineering Nanjing University of Science and TechnologyNanjingChina

The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent ***,there are still some limitations,including limited diversity of image style,distortion of detailed texture,unbalanced color tone,and lengthy training *** address these issues,we propose an asymmetric pre-training and fine-tuning(APF)-GAN model.

关键词： tuning network asymmetric

Granger causal representation learning for groups of time series

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science China(Information sciences) 2024年第5期67卷 56-68页

作者： Ruichu CAI Yunjin WU Xiaokai HUANG Wei CHEN Tom Z.J.FU Zhifeng HAO school of computer science Guangdong University of Technology Peng Cheng Laboratory college of science Shantou University

Discovering causality from multivariate time series is an important but challenging *** existing methods focus on estimating the Granger causal structures among multivariate time series,while ignoring the prior knowledge of these time series, e.g., the group of the time series. Focusing on discovering the Granger causal structures among groups of time series, we propose a Granger causal representation learning method to solve this problem. First, we use the multiset canonical correlation analysis method to learn the Granger causal representation of each group of time series. Then, we model the Granger causal relationships among the learned Granger causal representations using a recurrent neural network with temporal information. Finally, we formulate the above two stages into one unified optimization problem, which is efficiently solved using the augmented Lagrangian method. We conduct extensive experiments on synthetic and real-world datasets to validate the correctness and effectiveness of the proposed method.

关键词： Granger causal discovery Granger causal representation learning time series data recurrent neural network multiset canonical correlation analysis

SwiftTheft: A Time-Efficient Model Extraction Attack Framework Against Cloud-Based Deep Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 90-100页

作者： Wenbin YANG Xueluan GONG Yanjiao CHEN Qian WANG Jianshuo DONG school of Cyber science and Engineering Wuhan University school of computer science Wuhan University college of Electrical Engineering Zhejiang University

With the rise of artificial intelligence and cloud computing, machine-learning-as-a-service platforms,such as Google, Amazon, and IBM, have emerged to provide sophisticated tasks for cloud applications. These proprietary models are vulnerable to model extraction attacks due to their commercial value. In this paper, we propose a time-efficient model extraction attack framework called Swift Theft that aims to steal the functionality of cloud-based deep neural network models. We distinguish Swift Theft from the existing works with a novel distribution estimation algorithm and reference model settings, finding the most informative query samples without querying the victim model. The selected query samples can be applied to various cloud models with a one-time selection. We evaluate our proposed method through extensive experiments on three victim models and six datasets, with up to 16 models for each dataset. Compared to the existing attacks, Swift Theft increases agreement(i.e., similarity) by 8% while consuming 98% less selecting time.

关键词： Performance evaluation Cloud computing Analytical models Computational modeling Estimation Artificial neural networks Artificial intelligence

MSADCN:Multi-Scale Attentional Densely Connected Network for Automated Bone Age Assessment

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computers, Materials & Continua 2024年第2期78卷 2225-2243页

作者： Yanjun Yu Lei Yu Huiqi Wang Haodong Zheng Yi Deng college of computer and Information science Chongqing Normal UniversityChongqing401331China college of Mathematics and statistics Chongqing UniversityChongqing401331China

Bone age assessment(BAA)helps doctors determine how a child’s bones grow and develop in clinical *** BAA methods rely on clinician expertise,leading to time-consuming predictions and inaccurate *** deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional *** operation is costly and *** address these problems,we propose a multi-scale attentional densely connected network(MSADCN)in this *** constructs a multi-scale dense connectivity mechanism,which can avoid overfitting,obtain the local features effectively and prevent gradient vanishing even in limited training ***,MSADCN designs multi-scale structures in the densely connected network to extract fine-grained features at different ***,coordinate attention is embedded to focus on critical features and automatically locate the regions of interest(ROI)without additional *** addition,to improve the model’s generalization,transfer learning is applied to train the proposed MSADCN on the public dataset IMDB-WIKI,and the obtained pre-trained weights are loaded onto the Radiological Society of North America(RSNA)***,label distribution learning(LDL)and expectation regression techniques are introduced into our model to exploit the correlation between hand bone images of different ages,which can obtain stable age *** experiments confirm that our model can converge more efficiently and obtain a mean absolute error(MAE)of 4.64 months,outperforming some state-of-the-art BAA methods.

关键词： Bone age assessment deep learning attentional densely connected network muti-scale

CONSERVATIVE CONFORMING AND NONCONFORMING VEMS FOR FOURTH ORDER NONLINEAR SCHRODINGER EQUATIONS WITH TRAPPED TERM

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Journal of Computational Mathematics 2024年第2期42卷 454-499页

作者： Meng Li Jikun Zhao Zhongchi Wang Shaochun Chen school of Mathematics and statistics Zhengzhou UniversityZhengzhou 450001China school of computer science and Engineering Beihang universityBeijing 100083China

This paper aims to construct and analyze the conforming and nonconforming virtual element methods for a class of fourth order nonlinear Schrodinger equations with trapped *** mainly consider three types of virtual elements,including H^(2) conforming virtual element,C^(0) nonconforming virtual element and Morley-type nonconforming virtual *** fully discrete schemes are constructed by virtue of virtual element methods in space and modified Crank-Nicolson method in *** prove the mass and energy conservation,the boundedness and the unique solvability of the fully discrete *** introducing a new type of the Ritz projection,the optimal and unconditional error estimates for the fully discrete schemes are presented and ***,two numerical examples are investigated to confirm our theoretical analysis.

关键词： H^(2)conforming virtual element C^(0)nonconforming virtual element Morleytype nonconforming virtual element Nonlinear Schrodinger equation Conservation Convergence

Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian JIANG Xiujuan LEI Yi PAN Chunyan JI Wei JIANG college of Information science and Engineering Hunan Normal University school of computer science Shaanxi Normal University Faculty of computer science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences computer science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drugs Training Proteins Measurement Message passing Prediction methods Graph neural networks

BSTFNet:An Encrypted Malicious Traffic Classification Method Integrating Global Semantic and Spatiotemporal Features

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computers, Materials & Continua 2024年第3期78卷 3929-3951页

作者： Hong Huang Xingxing Zhang Ye Lu Ze Li Shaohua Zhou school of computer science and Engineering Sichuan University of Science&EngineeringYibin644002China school of Mathematics and statistics Sichuan University of Science&EngineeringYibin644002China

While encryption technology safeguards the security of network communications,malicious traffic also uses encryption protocols to obscure its malicious *** address the issues of traditional machine learning methods relying on expert experience and the insufficient representation capabilities of existing deep learning methods for encrypted malicious traffic,we propose an encrypted malicious traffic classification method that integrates global semantic features with local spatiotemporal features,called BERT-based Spatio-Temporal Features Network(BSTFNet).At the packet-level granularity,the model captures the global semantic features of packets through the attention mechanism of the Bidirectional Encoder Representations from Transformers(BERT)*** the byte-level granularity,we initially employ the Bidirectional Gated Recurrent Unit(BiGRU)model to extract temporal features from bytes,followed by the utilization of the Text Convolutional Neural Network(TextCNN)model with multi-sized convolution kernels to extract local multi-receptive field spatial *** fusion of features from both granularities serves as the ultimate multidimensional representation of malicious *** approach achieves accuracy and F1-score of 99.39%and 99.40%,respectively,on the publicly available USTC-TFC2016 dataset,and effectively reduces sample confusion within the Neris and Virut *** experimental results demonstrate that our method has outstanding representation and classification capabilities for encrypted malicious traffic.

关键词： Encrypted malicious traffic classification bidirectional encoder representations from transformers text convolutional neural network bidirectional gated recurrent unit

Blockchain-Based Certificateless Bidirectional Authenticated Searchable Encryption Scheme in Cloud Email System

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computer Modeling in Engineering & sciences 2024年第6期139卷 3287-3310页

作者： Yanzhong Sun Xiaoni Du Shufen Niu Xiaodong Yang college of Mathematics and statistics Northwest Normal UniversityLanzhou730070China college of computer science and Engineering Northwest Normal UniversityLanzhou730070China

Traditional email systems can only achieve one-way communication,which means only the receiver is allowed to search for emails on the email *** this paper,we propose a blockchain-based certificateless bidirectional authenticated searchable encryption model for a cloud email system named certificateless authenticated bidirectional searchable encryption(CL-BSE)by combining the storage function of cloud server with the communication function of email *** the new model,not only can the data receiver search for the relevant content by generating its own trapdoor,but the data owner also can retrieve the content in the same ***,there are dual authentication functions in our ***,during encryption,the data owner uses the private key to authenticate their identity,ensuring that only legal owner can generate the keyword ***,the blockchain verifies the data owner’s identity by the received ciphertext,allowing only authorized members to store their data in the server and avoiding unnecessary storage space *** obtain a formal definition of CL-BSE and formulate a specific scheme from the new system *** the security of the scheme is analyzed based on the formalized security *** results demonstrate that the scheme achieves multikeyword ciphertext indistinguishability andmulti-keyword trapdoor privacy against any adversary *** addition,performance evaluation shows that the new scheme has higher computational and communication efficiency by comparing it with some existing ones.

关键词： Cloud email system authenticated searchable encryption blockchain-based designated server test multi-trapdoor privacy multi-ciphertext indistinguishability