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processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
query processing » pre processing (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
ipca algorithm » wgcna algorithm (Expand Search), cscap algorithm (Expand Search), ii algorithm (Expand Search)
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level coding » level according (Expand Search), level modeling (Expand Search), level using (Expand Search)
Showing 61 - 80 results of 314 for search '(( element ipca algorithm ) OR ((( query processing algorithm ) OR ( level coding algorithm ))))', query time: 0.34s Refine Results
  1. 61
    Code snippet from “Netty/Buffer” Maven artefact.

    Code snippet from “Netty/Buffer” Maven artefact. by Matthew Yit Hang Yeow (20721206)

    Published 2025
    “…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”
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  2. 62
    Horizontal coding of milling parameters.

    Horizontal coding of milling parameters. by Nanqi Li (11640083)

    Published 2025
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  3. 63
    Model code

    Model code by Waltraud Schulze (20695250)

    Published 2025
    “…The latter provides insights into the inherent texture complexity of the image data due to the lossless coding. For classification of leaf surfaces from tree species based on the computed features, we utilized the k-nearest neighbors (kNN) algorithm with k=3. …”
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  4. 64
    Heatmap illustrating which multi-scale feature pixels were classified as “cell” by query selection. This data was collected by processing the full test set containing 29 movies from the bacterial mother machine dataset with Cell-TRACTR. Note that for these movies, the model preferentially uses pixels from the lowest resolution multi-scale features. The black pixel at the top corresponds to the top of the mother machine image where there are not usually cells.

    Heatmap illustrating which multi-scale feature pixels were classified as “cell” by query selection. This data was collected by processing the full test set containing 29 movies fro... by Owen M. O’Connor (11965460)

    Published 2025
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  5. 65
    Flowchart of system algorithm.

    Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

    Published 2025
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  6. 66
    Data Sheet 1_Strategies for population-level identification of post-acute sequelae of COVID-19 through health administrative data.pdf

    Data Sheet 1_Strategies for population-level identification of post-acute sequelae of COVID-19 through health administrative data.pdf by Cristina Mazzali (22090328)

    Published 2025
    “…From each included study, we extracted data on design, algorithms used for outcome identification (sources, coding systems, codes, time criteria/thresholds), and whether significant associations with SARS-CoV-2 infection were reported.…”
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  7. 67
    Code snippet from “Apache Dubbo” GitHub project.

    Code snippet from “Apache Dubbo” GitHub project. by Matthew Yit Hang Yeow (20721206)

    Published 2025
    “…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”
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  8. 68
    Mechanomics Code - JVT

    Mechanomics Code - JVT by Carlo Vittorio Cannistraci (5854046)

    Published 2025
    “…At the beginning of the code, there is a help section that explains how to use it.…”
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  9. 69
    Visualization of algorithm detection results.

    Visualization of algorithm detection results. by Xinpeng Yao (18882573)

    Published 2025
    “…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”
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  10. 70
    An overview of the organization of the study program.

    An overview of the organization of the study program. by Marialuisa Gandolfi (8639238)

    Published 2024
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  11. 71
    Overview of the development of the biomarkers in the motor, exteroceptive, interoceptive, and cerebral domains.

    Overview of the development of the biomarkers in the motor, exteroceptive, interoceptive, and cerebral domains. by Marialuisa Gandolfi (8639238)

    Published 2024
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  12. 72
    The schedule of enrolment, interventions, and assessments.

    The schedule of enrolment, interventions, and assessments. by Marialuisa Gandolfi (8639238)

    Published 2024
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  13. 73
    Parameters of stimuli used in the study.

    Parameters of stimuli used in the study. by Elnaz Nemati (21402730)

    Published 2025
    “…<div><p>This study introduces a neurobiologically inspired computational model based on the predictive coding algorithm, providing insights into coherent motion detection processes. …”
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  14. 74
    AI-SSRF-SP (Artificial Intelligence - SSRF - Superfacility Platform) developed by the Big Data Science Center (BDSC) at Shanghai Synchrotron Radiation Facility (SSRF)

    AI-SSRF-SP (Artificial Intelligence - SSRF - Superfacility Platform) developed by the Big Data Science Center (BDSC) at Shanghai Synchrotron Radiation Facility (SSRF) by Alessandro Sepe (10304915)

    Published 2025
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  15. 75
    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived from the 3-level wavelet transform (WT) at four resolutions. These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms. The heat map (on the right) is the correlation matrix after feature selection, in which features whose Pearson’s correlation coefficient is higher than 0.8 are considered highly correlated. We keep only one representative feature and remove its highly correlated features.

    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived... by Quang Dung Dinh (20995766)

    Published 2025
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  16. 76
    Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase algorithm for multi-material topology optimization [34]. (c) A new mapping based interpolation function for multi-material topology optimization [35]. (d) A material-field series expansion (MFSE) model for multi-material topology optimization [36].

    Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

    Published 2025
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  17. 77
    Survey data.

    Survey data. by Tebogo T. Mamalelala (19254175)

    Published 2024
    “…This study used a cross-sectional survey design to query healthcare workers in Kweneng District, Botswana about perceived PASC prevalence, duration, symptoms, impact, and management strategies. …”
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  18. 78
    Demographic characteristics of participants.

    Demographic characteristics of participants. by Tebogo T. Mamalelala (19254175)

    Published 2024
    “…This study used a cross-sectional survey design to query healthcare workers in Kweneng District, Botswana about perceived PASC prevalence, duration, symptoms, impact, and management strategies. …”
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  19. 79
    Most common symptom, as reported by respondents.

    Most common symptom, as reported by respondents. by Tebogo T. Mamalelala (19254175)

    Published 2024
    “…This study used a cross-sectional survey design to query healthcare workers in Kweneng District, Botswana about perceived PASC prevalence, duration, symptoms, impact, and management strategies. …”
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  20. 80
    Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset.

    Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

    Published 2024
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