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1901
Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy
Published 2025-07-01“…Abstract Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by the convergence angle of nanoscale focusing optics which creates simultaneous dependency of the far-field scattering data on three independent components of the local strain tensor—corresponding to dilation and two potential rigid body rotations of the unit cell. …”
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1902
Interpretive Structural Modeling of Factors Affecting Organizational Ambidexterity in the Ministry of Sports and Youth
Published 2022-07-01“…The statistical population of this study consisted of experts who were selected purposefully based on theoretical saturation of 15 of them. Semi-structured interviews were used to collect data in the qualitative study and a questionnaire was used to collect data in the quantitative study. …”
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1903
Retracted: Internet of Things Health Detection System in Steel Structure Construction Management
Published 2020-01-01“…It is concluded that the time series model established in this study can objectively reflect the change trend and law of strain data, has certain prediction accuracy, and has certain value significance for monitoring data analysis and construction management of steel building structures.…”
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1904
Intelligent Identification of Structural Damage Based on the Curvature Mode and Wavelet Analysis Theory
Published 2021-01-01“…Data fitting is then performed to estimate the degree of structural damage. …”
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1905
Predictive modeling of visible-light azo-photoswitches’ properties using structural features
Published 2025-04-01“…Abstract In this manuscript we present the strategy for modeling photoswitch properties (maximum absorption wavelength and thermal half-life of photoisomers) of visible-light azo-photoswitches using structural data. We compile a comprehensive data set from literature sources and perform a rigorous benchmark to select the best feature type and modeling approach. …”
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1906
Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning
Published 2025-02-01Get full text
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1907
Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning
Published 2020-11-01“…Based on this algorithm, correlation considerations can be performed on the data structure, the measured variables, and the diagnostic parameters. …”
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1908
Structural Constraints in Current Stomatal Conductance Models Preclude Accurate Prediction of Evapotranspiration
Published 2024-08-01“…In contrast, a ML approach, wherein the model structure is learned from the data, outperforms traditional models, thus highlighting that there still is significant room for improvement in the structure of traditional models for predicting ET. …”
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1909
Enhancing structural health monitoring with machine learning for accurate prediction of retrofitting effects
Published 2024-10-01“…This research aimed to develop a methodology for training an artificial intelligence (AI) system to predict the effects of retrofitting on civil structures, using data from the KW51 bridge (Leuven). …”
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1910
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1911
Calculation of Water Saturation of Dolomite Reservoir Based on Multi-Pore Structure Model
Published 2025-06-01“…The total conductivity of the rock is established by the parallel combination of the effective components to establish the porous structure response equation, the equation is fitted by the rock electrical experimental data, and the parameters such as the fracture porosity index (mj) and the interconnected void porosity (ml) are calculated. …”
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1912
THE METHOD OF ADAPTIVE STATISTICAL CODING TAKING INTO ACCOUNT THE STRUCTURAL FEATURES OF VIDEO IMAGES
Published 2024-12-01“…To reduce the output volume, the RLE algorithm and integral arithmetic coding are adapted to the new structure of the input data. Thus, the method of linearization of two-dimensional transformants based on zig-zag scanning was further developed. …”
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1913
From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning
Published 2025-05-01“…The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. …”
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1914
Synthesis and structural study of the Linde Type-A zeolite prepared from kaolinite
Published 2016-12-01“…The measured hkl and intensity data sets are the inputs for structure determination. …”
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1915
Deep nested U-structure network with frequency attention for building semantic segmentation
Published 2025-08-01“…We have introduced a novel approach to address these issues: an end-to-end residual U-structure embedded within a U-Net, enhanced by a frequency attention module and a hybrid loss function. …”
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1916
Local Scouring Visualization of Bed Channel Surface in Hydraulic Structure Using Surfer
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1917
Spearman Rank Correlation PCA for Mixed Scale Indicator in Structural Equation Modeling
Published 2025-03-01“…Structural Equation Modeling (SEM) is a statistical modeling technique that integrates measurement models and structural models simultaneously. …”
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1918
Durability Test and Service Life Prediction Methods for Silicone Structural Glazing Sealant
Published 2025-05-01“…Silicone structural glazing (SSG) sealants are crucial sealing materials in modern building curtain walls, whose performance degradation may lead to functional and safety issues, posing significant challenges to building safety maintenance. …”
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1919
Research on Structure and Characteristics of Gear System of Crossflow in Flow Domain of Reactor Core
Published 2024-11-01“…However, in traditional research, the states of flow resistance, thermal resistance, flow mixing and other states are measured by the macroscopic integration of lines, surfaces and volumes, and the fine data of tens of millions or hundreds of millions of computing grids are mostly converted into hundreds or thousands of sets of average data, the physical state is reduced from three-dimensional to two-dimensional or one-dimensional state, and the spatial resolution is reduced from submillimeter to decimeter or lower, and the fine data cannot be effectively and fully utilized. …”
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1920
Co-methylation networks associated with cognition and structural brain development during adolescence
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