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Code context-based reviewer recommendation

Frontiers of computer science 2025年第1期19卷 97-108页

作者： Dawei YUAN Xiao PENG Zijie CHEN Tao ZHANG Ruijia LEI School of Computer Science and Engineering Macao University of Science and TechnologyMacao 999078China Faculty of Science University of AmsterdamAmsterdam WB 1018Netherlands

Code review is a critical process in software development, contributing to the overall quality of the product by identifying errors early. A key aspect of this process is the selection of appropriate reviewers to scrutinize changes made to source code. However, in large-scale open-source projects, selecting the most suitable reviewers for a specific change can be a challenging task. To address this, we introduce the Code Context Based Reviewer Recommendation (CCB-RR), a model that leverages information from changesets to recommend the most suitable reviewers. The model takes into consideration the paths of modified files and the context derived from the changesets, including their titles and descriptions. Additionally, CCB-RR employs KeyBERT to extract the most relevant keywords and compare the semantic similarity across changesets. The model integrates the paths of modified files, keyword information, and the context of code changes to form a comprehensive picture of the changeset. We conducted extensive experiments on four open-source projects, demonstrating the effectiveness of CCB-RR. The model achieved a Top-1 accuracy of 60%, 55%, 51%, and 45% on the Android, OpenStack, QT, and LibreOffice projects respectively. For Mean Reciprocal Rank (MRR), CCB achieved 71%, 62%, 52%, and 68% on the same projects respectively, thereby highlighting its potential for practical application in code reviewer recommendation.

关键词： code reviewer recommendation code context pull request

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A Generative Model-Based Network Framework for Ecological Data Reconstruction

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computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen School of Electronic and Information Engineering University of Science and Technology LiaoningAnshan114051China School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction

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Revisiting the alpha-decay reduced width of the lightest uranium isotope 214U

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Chinese Physics C 2025年第3期49卷 107-114页

作者： Shuangshuang Zhang Yongjia Wang Xiaotao He College of Materials Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 210016China School of Science Huzhou UniversityHuzhou 313000China

The lightest uranium isotope^(214)U has been produced at the Heavy lon Research Facility in Lanzhou,*** a-decay reduced width($2)of^(214)U has been found to be significantly larger than those of other nuclei by a factor of ***,the extraction ofσ^(2)depends on the penetration probability(P)through the barrier,and P is related to the theoretical method of obtaining it and the form of theα-core *** aim of this study is to investigate whether the selections of theα-core potential and the method of calculating P can affect the above *** different phenomenological a-core potentials and two microscopic double-folding potentials,together with the Wentzel-Kramers-Brillouin(WKB)approximation and transfer matrix(TM)approach,are used to obtain *** value of P obtained using the WKB approximation is about 20%-40%smaller than the one obtained using the TM ***,the deduced s2 is *** choice of a-core potential can significantly affect the value ofσ^(2).With the spherical form for theα-core potentials,theσ^(2)of^(214)U obtained with both the WKB and TM approaches are about twice as large as those of the surrounding *** the deformed double-folding potential,the ratio between 32 of^(214)U and that of the surrounding nuclei is observed to be slightly belowσ^(2).The effects of nuclear deformation and theα-core potential should be considered when studying theα-decay reduced width in the NpNn systematics.

关键词： alpha decay reduced width penetration probability

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Innovative Cement-Free Alkali-Activated Concrete: A Study on Ultra-Rapid Hardening under Negative Temperature Curing Condition

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ce/papers 2025年第2期8卷 145-152页

作者： Xiang, Bin Guo, Xun Yang, Mingyu Zhou, Jiehang Lai, Jianzhong School of Materials Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

Conventional silicate cement is difficult to use in extremely cold regions. But alkali-activated slag concrete (AASC) can use alkali-activated chemistry to accelerate the production of C-A-S-H cementitious materials, resulting in high mechanical properties in a short period of time. In this paper, it investigated the static mechanical properties of alkali-activated slag concrete with different CaO contents and insulation methods under low-temperature conditions (-15 °C). It was shown that when the CaO content was 2%, the flexural strength of the concrete with a curing time of only 4h was 9.20 MPa, the compressive strength was 47.6 MPa. Both in the fully wrapped insulation method and the upper and lower wrapped insulation method could be used in low temperature conditions. The flexural strengths of both methods were 9.90 MPa and 8.93 MPa in 4 h. Their compressive strengths were 59.1 MPa and 66.53 MPa, respectively. Therefore, AASC can achieve ideal strength at low temperatures. It is a building material that can be used under extreme conditions. © 2025 Ernst & Sohn GmbH.

关键词： Compressive strength

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Impact resistance of foam concrete gradient composite panels

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ce/papers 2025年第2期8卷 138-144页

作者： Guo, Xun Xiang, Bin Zhou, Jiehang Yang, Mingyu Lai, Jianzhong School of Materials Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

Foam concrete has the advantages of energy and shock absorption which can be used as an impact resistant material. This article designed a three-layer concrete gradient structure and analyzed the failure mechanism of the structure. Finally it investigated impact resistance of concrete without aggregate and foam concrete with lightweight aggregate. The results show that compared with normal concrete, foam concrete has excellent impact resistance. The final cracking energy of the composite panel increased by 10% and 4.4% at different heights, respectively. The impact resistance of foam concrete without aggregate was better than that of foam concrete with lightweight aggregate, and the final cracking energy increased by 148.3% and 132.6%. Combined with macro analysis, it is found that the higher the porosity of foam concrete benefited the impact resistance of foam concrete. Therefore, this three-layer concrete composite panel is a potential protective material for daily construction and even other special occasions. © 2025 Ernst & Sohn GmbH.

关键词： Cracks

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Towards Maximizing Semantic Coverage for Image-Text Retrieval

Towards Maximizing Semantic Coverage for Image-Text Retrieva...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Xu, Junhao Liu, Zheng Chen, Zhumin Shen, Fei School of Computer Science and Technology Shandong University China School of Computer Science and Technology Shandong University of Finance and Economics China School of Computer Science and Engineering Nanjing University of Science and Technology China

ISBN: (纸本)9798350368741

To establish semantic associations between images and texts, existing Image-Text Retrieval (ITR) methods primarily focus on fixed-scale fragments, which only identify explicit semantic categories. Consequently, semantic coverage is constrained, leading to the omission of certain semantic associations. To enlarge the semantic coverage, we propose the Semantic Coverage-Aware Network (SCA-Net). First, explicit semantic categories are identified by SCA-Net through analyzing the semantic membership of visual and textual fragments, thereby establishing more precise explicit semantic associations. Second, implicit semantic categories are identified by SCA-Net via adaptively aggregating visual and textual fragments across various scales using a co-occurrence-aware router, thereby significantly expanding the semantic coverage and establishing complete semantic associations. Third, image-text similarity is calculated using the attention mechanism over a broader range of semantic coverage. Extensive experiments demonstrate that SCA-Net significantly enhances ITR performance compared to state-of-the-art methods by maximizing semantic coverage. © 2025 IEEE.

关键词： Co-occurrence-aware router Image-text retrieval Semantic association Semantic category Semantic coverage

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B+-Tree-Quantization-Based Shared Secret Key Extraction Scheme From Atmospheric Optical Wireless Channel

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IEEE Transactions on Communications 2025年第5期73卷 3394-3408页

作者： Pan, Gang Chen, Chunyi Changchun University of Science and Technology School of Computer Science and Technology Changchun130022 China Changchun University of Science and Technology School of Computer Science and Technology Key Laboratory of Photoelectric Measurement & Control and Optical Information Transfer Technology Changchun130022 China Chongqing Research Institute Changchun University of Science and Technology Chongqing401135 China

To reduce key disagreement rate and increase key generation rate, this paper proposes a lightweight and robust shared secret key extraction scheme from atmospheric optical wireless channel. A conception of grouping samples by using B+ tree and quantizing groups is introduced to improve the balance of distribution of channel measurement values in quantization intervals. Based on the conception, a basic B+ tree quantization algorithm (B-BPTQ) and a compensation-technology-based B+ tree quantization algorithm (C-BPTQ) are designed. A LDPC-based multi-scale information reconciliation algorithm (LDPC-MSIR) is put forward to simplify information reconciliation and reduce its computation complexity. An enhanced randomness post-processing algorithm is formulated to increase statistical randomness of initial key sequence. Finally, the performance of the proposed scheme is validated by numerical simulations and field experiments. The experimental results show that it has better performance in terms of key disagreement rate, key generation rate and key randomness compared with other schemes. © 1972-2012 IEEE.

关键词： Optical communication

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Experimental investigation on the anti-detonation performance of composite structure containing foam geopolymer backfill material

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Defence technology(防务技术) 2025年第1期43卷 304-318页

作者： Hang Zhou Hujun Li Zhen Wang Dongming Yan Wenxin Wang Guokai Zhang Zirui Cheng Song Sun Mingyang Wang School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China College of Civil Engineering and Architecture Zhejiang UniversityHangzhou 310058China Institute for Composites Science Innovation School of Materials Science and EngineeringZhejiang UniversityHangzhou310027China School of Safety Science and Engineering(School of Emergency Management) Nanjing University of Science and TechnologyNanjing 210094China State Key Laboratory of Disaster Prevention and Mitigation of Explosion and Impact Army Engineering University of PLANanjing 210014China

The compression and energy absorption properties of foam geopolymers increase stress wave attenuation under explosion impacts,reducing the vibration effect on the *** tests were conducted using several composite structure models,including a concrete lining structure(CLS)without foam geopolymer and six foam geopolymer composite structures(FGCS)with different backfill parameters,to study the dynamic response and wave dissipation mechanisms of FGCS under explosive ***,strain,and vibration responses at different locations were synchronously *** damage modes and dynamic responses of different models were compared,and how wave elimination and energy absorption efficiencies were affected by foam geopolymer backfill parameters was *** results showed that the foam geopolymer absorbed and dissipated the impact energy through continuous compressive deformation under high strain rates and dynamic loading,reducing the strain in the liner structure by 52%and increasing the pressure attenuation rate by 28%.Additionally,the foam geopolymer backfill reduced structural vibration and liner deformation,with the FGCS structure showing 35%less displacement and 70%less acceleration compared to the *** FGCS model with thicker,less dense foam geopolymer backfill,having more pores and higher porosity,demonstrated better compression and energy absorption under dynamic impact,increasing stress wave attenuation *** analyzing the stress wave propagation and the compression characteristics of the porous medium,it was concluded that the stress transfer ratio of FGCS-ρ-579 was 77%lower than that of CLS,and the transmitted wave energy was 90%*** results of this study provide a scientific basis for optimizing underground composite structure interlayer parameters.

关键词： Explosion load Composite structure Geopolymer foam Energy absorption

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GMS:A Novel Method for Detecting Reentrancy Vulnerabilities in Smart Contracts

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computers, Materials & Continua 2025年第5期83卷 2207-2220页

作者： Dawei Xu Fan Huang Jiaxin Zhang Yunfang Liang Baokun Zheng Jian Zhao School of Computer Science Changchun UniversityChangchun130012China School of Computer Science and Technology Beijing Institute of TechnologyBeijing100081China School of InformationManagement for Law China University of Political Science and LawBeijing102249China

With the rapid proliferation of Internet ofThings(IoT)devices,ensuring their communication security has become increasingly *** and smart contract technologies,with their decentralized nature,provide strong security guarantees for ***,at the same time,smart contracts themselves face numerous security challenges,among which reentrancy vulnerabilities are particularly *** detection tools for reentrancy vulnerabilities often suffer from high false positive and false negative rates due to their reliance on identifying patterns related to specific transfer *** address these limitations,this paper proposes a novel detection method that combines pattern matching with deep ***,we carefully identify and define three common patterns of reentrancy vulnerabilities in smart ***,we extract key vulnerability features based on these ***,we employ a Graph Attention Neural Network to extract graph embedding features from the contract graph,capturing the complex relationships between different components of the ***,we use an attention mechanism to fuse these two sets of feature information,enhancing the weights of effective information and suppressing irrelevant information,thereby significantly improving the accuracy and robustness of vulnerability *** results demonstrate that our proposed method outperforms existing state-ofthe-art techniques,achieving a 3.88%improvement in accuracy compared to the latest vulnerability detection model AME(Attentive Multi-Encoder Network).This indicates that our method effectively reduces false positives and false negatives,significantly enhancing the security and reliability of smart contracts in the evolving IoT ecosystem.

关键词： Smart contract Internet of Things reentrancy vulnerabilities graph neural network

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Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

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