Study on the Evaluation Method of Collaborative Dust Prevention Effect with Coal Miners-Based on Feature Reduction, Genetic Algorithm, and Backpropagation. [PDF]
Saf Health WorkShi S, Zheng H, Li H, Wang X.
europepmc +1 more source
Irrigation and Drainage, EarlyView.ABSTRACT Accurate estimation of reference evapotranspiration (ET0) and crop coefficients (Kc) is critical for irrigation planning, particularly in data‐limited regions where agriculture dominates freshwater consumption. Although machine learning (ML) methods have been widely applied to ET0 and Kc estimation, most studies address these parameters ...
Ilker Angin +4 more
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A Multi-Branch Training Strategy for Enhancing Neighborhood Signals in GNNs for Community Detection. [PDF]
Entropy (Basel)Guo Y, Wu Q, Lü L.
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Journal of Magnetic Resonance Imaging, EarlyView.ABSTRACT Background The demand for cardiac MRI is increasing with the growing burden of cardiovascular disease. However, conventional protocols require sequential acquisitions for multi‐breath‐hold 2D cine and 3D MR angiography (MRA), which is time‐consuming.
Ruixin Chen +7 more
wiley +1 more source
Visual classification of allergenic pollen in iteratively reconstructed lens-less DIHM images. [PDF]
Sci RepCugmas B +5 more
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3D Surface Profiling via Direct End‐to‐End Regression With a Photonic Geometric Sensor
Laser &Photonics Reviews, EarlyView.Measurements of microscale surface patterns are essential for quality control across semiconductor and biomedical industries, yet the development of miniaturized, intelligent systems remains constrained by the complexity and bulkiness of conventional benchtop metrology.
Ziyao Zhang +13 more
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Influencing factors for childbirth readiness among pregnant women based on the reciprocal determinism theory and backpropagation neural network: a cross-sectional study in China. [PDF]
BMC Pregnancy ChildbirthMengmei Y +4 more
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Laser &Photonics Reviews, EarlyView.Neural networks can accelerate modeling and inverse design of electromagnetic devices by several orders of magnitude, but usually require large amounts of data to train. This work demonstrates that integrating knowledge about quasinormal modes into the network architecture reduces the required amount of training data significantly, while simultaneously
Viktor A. Lilja +3 more
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Deep-Learning- versus Hypothesis-Driven Modeling in Model-Informed Drug Development: A PK/PD Case Study. [PDF]
J Clin PharmacolGomeni R, Bressolle-Gomeni F.
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Macromolecular Rapid Communications, EarlyView.When seeking nanoparticles with elevated drug loading content, the experimental setup, including solvent selection, is crucial. Through machine learning, we pinpointed that the drug's solubility in the organic solvent is the key factor for attaining high drug loading content.
Wei Ge +4 more
wiley +1 more source