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  1. 21

    Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

    Published 2023-01-01
    “…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%~22.32% and 1.86%~16.69% respectively, which is superior to the existing method.…”
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  2. 22

    Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

    Published 2023-01-01
    “…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%~22.32% and 1.86%~16.69% respectively, which is superior to the existing method.…”
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    Article
  3. 23

    Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor Imagery Protocols by Alkinoos Athanasiou, Chrysa Lithari, Konstantina Kalogianni, Manousos A. Klados, Panagiotis D. Bamidis

    Published 2012-01-01
    “…Event-Related Desynchronization/Synchronization (ERD/ERS) of the mu-rhythm was used to evaluate MI performance. Source detection and FCNs were studied with eConnectome. …”
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  6. 26

    Selenium Accumulating Leafy Vegetables Are a Potential Source of Functional Foods by Petro E. Mabeyo, Mkabwa L. K. Manoko, Amra Gruhonjic, Paul A. Fitzpatrick, Göran Landberg, Máté Erdélyi, Stephen S. Nyandoro

    Published 2015-01-01
    “…., Cucurbita maxima, Ipomoea batatas, Solanum villosum, Solanum scabrum, and Vigna unguiculata were explored for their capabilities to accumulate selenium when grown on selenium enriched soil and for use as a potential source of selenium enriched functional foods. Their selenium contents were determined by spectrophotometry using the complex of 3,3′-diaminobenzidine hydrochloride (DABH) as a chromogen. …”
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  7. 27

    Derivation of pressure distribution models for horizontal well using source function by J.O. Oloro, E.S. Adewole

    Published 2019-05-01
    “…In this work, ten (10) models for pressure distribution for horizontal well under different boundary variation were derived following these steps for each of the models:(i) choosing a boundary condition for each axis (ii) selecting the appropriate source function for each axis and (iii)applying Newman product rule to arrive at the pressure expression. …”
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  8. 28

    Go Source Code Vulnerability Detection Method Based on Graph Neural Network by Lisha Yuan, Yong Fang, Qiang Zhang, Zhonglin Liu, Yijia Xu

    Published 2025-06-01
    “…With the widespread application of the Go language, the demand for vulnerability detection in Go programs is increasing. Existing detection models and methods have deficiencies in extracting source code features of Go programs and mainly focus on detecting concurrency vulnerabilities. …”
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    Anomaly Usage Behavior Detection Based on Multi-Source Water and Electricity Consumption Information by Wenqing Zhou, Chaoqiang Chen, Qin Yan, Bin Li, Kang Liu, Yingjun Zheng, Hongming Yang, Hui Xiao, Sheng Su

    Published 2025-01-01
    “…Current resident anomaly detection technologies rely on single-source energy data, lacking detailed behavior pattern analysis. …”
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    Improved UAV Target Detection Model for RT-DETR by Yong He, Yufan Pang, Guolin Ou, Renfeng Xiao, Yifan Tang

    Published 2025-01-01
    “…Furthermore, the Focaler-MPDIoU loss function has been developed to address the challenge of suboptimal localization accuracy for hard-to-detect targets and diminutive targets. …”
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  14. 34

    Nitrogen-functionalized modulation of iron nanoparticles promotes selective hydrogenation of carbon dioxide by Xianbiao Wang, Jun Qian, Zixuan Lu, Jie Huang, Liru Zheng, Yong Jiang, Mengdie Cai, Yuxue Wei, Lisheng Guo, Song Sun

    Published 2025-03-01
    “…Nitrogen-functionalized iron nanoparticles were prepared using a one-pot hydrothermal process. …”
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  15. 35

    Enhanced Reward Function Design for Source Term Estimation Based on Deep Reinforcement Learning by Junhee Lee, Hongro Jang, Minkyu Park, Hyondong Oh

    Published 2025-01-01
    “…This study investigates the design of reward functions for deep reinforcement learning-based source term estimation (STE). …”
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  16. 36

    Framework development of continuous non-linear Diophantine fuzzy sets and its application to renewable energy source selection by Asaf Khan, Saifullah Khan, Ariana Abdul Rahimzai, Saleem Abdullah

    Published 2025-05-01
    “…We develop continuous non-linear Diophantine fuzzy algebraic aggregation operators and apply them to a multi-attribute decision-making problem in renewable energy source selection. A case study demonstrates the effectiveness of the proposed CN-LDFS framework using a weighted geometric operator. …”
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  17. 37

    MIF-YOLO: An Enhanced YOLO with Multi-Source Image Fusion for Autonomous Dead Chicken Detection by Jiapan Li, Yan Zhang, Yong Zhang, Hongwei Shi, Xianfang Song, Chao Peng

    Published 2025-12-01
    “…Addressing the paucity of automated systems for the detection of dead poultry within large-scale agricultural settings, characterized by the onerous and time-consuming manual inspection processes, this study introduces an enhanced YOLO algorithm with multi-source image fusion (MIF-YOLO) for the autonomous identification of dead chicken. …”
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  18. 38

    Crashing Fault Residence Prediction Using a Hybrid Feature Selection Framework from Multi-Source Data by Xiao Liu, Xianmei Fang, Song Sun, Yangchun Gao, Dan Yang, Meng Yan

    Published 2025-02-01
    “…This study introduces SCM, a two-stage composite feature selection framework designed to address this challenge. …”
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  19. 39

    SELECTION OF CRITERIA FOR ASSESSING THE EFFECTIVENESS OF RENEWABLE ENERGY SUPPORT POLICIES by N.А. Riazanova

    Published 2018-09-01
    “…The purpose of the article is to research and develop scientific and economic decisions on the assessment of the efficiency of the use of renewable energy sources, and to justify the selection of criteria for assessing renewable energy support policies. …”
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