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Showing 141 - 160 results of 53,088 for search '((structured OR structured) OR (structures OR structural)) data', query time: 0.17s Refine Results
  1. 141

    Model reduction of structural mechanical response in the time domain by Xin Yan, Xinyu Guo, Ningya He, Jinglong Shi, Daquan Zhao

    Published 2025-03-01
    “…Abstract A novel model reduction approach for analyzing structural mechanical response states in automotive systems is introduced, leveraging time-domain signal data from road testing. …”
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    UPN-GCN: Update Positive-Negative Graph Convolution Neural Network in Non-Euclidean Structured Data by Lijun Fan, Shichao Yi, Wenrui Guan, Pingxin Wang

    Published 2025-01-01
    “…Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have utilized GCNs for data with Euclidean structures. such as image data and language data, and achieved good results, expanding the application scope of GCN. …”
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    Disassembling-Based Structural Damage Detection Using Static Measurement Data by Eun-Taik Lee, Hee-Chang Eun

    Published 2019-01-01
    “…Damage detection methods can be classified into global and local approaches depending on the division of measurement locations in a structure. The former utilizes measurement data at all degrees of freedom (DOFs) for structural damage detection, while the latter utilizes data of members and substructures at a few DOFs. …”
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  12. 152

    Intra-BRICS Trade: A Panel Data Analysis with Structural Breaks by Alper Yılmaz

    Published 2022-12-01
    “…For this purpose, we employed the Westerlund and Edgerton cointegration approach to check for cointegration under structural breaks and the procedure for the asymmetric Granger non-causality test to assess the causal relationship between the custom tariff and export variables of BRICS countries with regard to the panel data methodology for the 2000-2020 period using annual data. …”
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  13. 153

    Board structure and bank performance: Evidence from Ethiopia by Alem Gebremedhin Berhe

    Published 2023-12-01
    Subjects: “…board structure…”
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    Enhancing Security of Databases through Anomaly Detection in Structured Workloads by Charanjeet Dadiyala, Faijan Qureshi, Kritika Anil Bhattad, Sourabh Thakur, Nida Tabassum Sharif Sheikh, Kushagra Anil Kumar Singh

    Published 2025-02-01
    “…One of the most advanced ways of enhancing database security is using an anomaly detection system, especially for structured workloads. Structured workloads typically exhibit predictable patterns of data access and usage, making them susceptible to displaying anomalies that may indicate unauthorized access, data manipulation, or other security breaches. …”
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  18. 158

    SMART: Structured Missingness Analysis and Reconstruction Technique for credit scoring by Seongil Han, Haemin Jung, Paul D. Yoo

    Published 2025-04-01
    “…Building on these developments, this study proposes a novel imputation approach, SMART (Structured Missingness Analysis and Reconstruction Technique) for credit scoring datasets. …”
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  19. 159

    Enhancing Security of Databases through Anomaly Detection in Structured Workloads by Charanjeet Dadiyala, Faijan Qureshi, Kritika Anil Bhattad, Sourabh Thakur, Nida Tabassum Sharif Sheikh, Kushagra Anil Kumar Singh

    Published 2025-02-01
    “…One of the most advanced ways of enhancing database security is using an anomaly detection system, especially for structured workloads. Structured workloads typically exhibit predictable patterns of data access and usage, making them susceptible to displaying anomalies that may indicate unauthorized access, data manipulation, or other security breaches. …”
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    Article
  20. 160

    Dynamics of link formation in networks structured on the basis of predictive terms by S. O. Kramarov, O. R. Popov, I. E. Dzhariev, E. A. Petrov

    Published 2023-06-01
    “…In order to model and analyze the information conductivity of complex networks having an irregular structure, it is possible to use percolation theory methods known in solid-state physics to quantify how close the given network is to a percolation transition, and thus to form a prediction model. …”
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