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    Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms by Anjan Kumar Pradhan, Prasad Gandham, Kanniah Rajasekaran, Niranjan Baisakh

    Published 2025-06-01
    “…Improved performances of the algorithms via feature selection from the raw gene features identified 235 unique genes as top candidate genes across all models for all stresses. …”
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  16. 9216

    Gradient vs. Non-Gradient-Based Model Free Control Algorithms: Analysis and Applications to Nonlinear Systems by Andrei Baciu, Corneliu Lazar

    Published 2025-03-01
    “…This title is assumed by two types of algorithms, which contain it in the name. One is the gradient-based algorithm, Model Free Adaptive Control, defined by Hou, which uses the concept of dynamic linearization through pseudo partial derivatives (PPD) and pseudo gradient (PG). …”
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  17. 9217

    A Lightweight Citrus Ripeness Detection Algorithm Based on Visual Saliency Priors and Improved RT-DETR by Yutong Huang, Xianyao Wang, Xinyao Liu, Liping Cai, Xuefei Feng, Xiaoyan Chen

    Published 2025-05-01
    “…To reduce computational overhead, we designed the E-CSPPC module, which efficiently combines cross-stage partial networks with gated and partial convolutions, combined with cascaded group attention (CGA) and inverted residual mobile block (iRMB), which minimizes model complexity and computational demand and simultaneously strengthens the model’s capacity for feature representation. …”
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  19. 9219

    A Comprehensive Algorithm for Evaluating Node Influences in Social Networks Based on Preference Analysis and Random Walk by Chengying Mao, Weisong Xiao

    Published 2018-01-01
    “…Based on the three basic centrality measures, a comprehensive algorithm named PARW-Rank for evaluating node influences has been proposed by applying preference relation analysis and random walk technique. …”
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  20. 9220

    Using Cohen Sutherland Line Clipping Algorithm to Generate 3D Models from 2D by Marah Taha

    Published 2020-05-01
    “…Most of the previous researches used the idea of ​​drawing by vanishing point to generate 3D objects from 2D environment, But the algorithm designed in this paper provides an idea of ​​how to draw three-dimensional shapes from two-dimensional drawings when applying Cohen Sutherland Line clipping algorithm, so that a basic two-dimensional shape is inserted from a set of points connected with each other must be within vision borders with a vanishing point outside of vision that is connected with all points of basic shape to consist a group of lines with partial intersections. …”
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