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1681
Debiasing Structure Function Estimates from Sparse Time Series of the Solar Wind: A Data-driven Approach
Published 2025-01-01“…Structure functions (SFs), which quantify the moments of increments of a stochastic process, are essential complementary statistics to power spectra for analyzing the self-similar behavior of a time series. …”
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1682
Grain Protein Function Prediction Based on CNN and Residual Attention Mechanism with AlphaFold2 Structure Data
Published 2025-02-01“…The experimental results indicate that secondary structure and spatial structure information contribute to improving model performance. …”
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1683
DETERMINANTS OF STRUCTURAL DIMENSION OF DAILY BEHAVIOUR IN A TRADITIONAL AFRICAN CITY: A CASE STUDY OF ILORIN, NIGERIA
Published 2013-10-01“…The study also shows clearly that the temporal structure of activity in Ilorin is different from what obtains in Western cities where there is flexibility in the usage of time. …”
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1684
SV-MeCa: an XGBoost-based meta-caller approach for structural variant calling from short-read data
Published 2025-08-01“…Abstract Background Calling structural variants (SVs), i.e., genomic alterations of $$\ge $$ 50bp, from whole genome short-read data remains challenging, as existing callers are known to lack accuracy and robustness. …”
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1685
Structural Characteristics of the Turning End of the Kaiping Syncline and Its Influence on Coal Mine Gas
Published 2024-12-01“…This study, drawing on previous theories, research, and practical coal mine production data, analyzes the structural characteristics of the Kaiping syncline, with particular emphasis on the structural differentiation at its northeastern uplifted end. …”
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1686
A structured-illumination reflectance imaging dataset for woody breast assessment of broiler meatZenodo
Published 2025-06-01“…An image dataset was created to assess WB conditions in broiler breast fillets using structured-illumination reflectance imaging (SIRI) as a non-destructive, objective means for WB assessment. …”
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1687
A Semi-Supervised Deep Network Embedding Approach Based on the Neighborhood Structure
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1688
A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen
Published 2024-12-01“…Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. …”
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1689
Damage Detection in Beam Structures Based on Frequency-Domain Analysis Methods for Nonlinear Systems
Published 2025-05-01“…To improve the accuracy of the Nonlinear Auto-Regressive with eXogenous inputs (NARX) model and reduce the impact of noise interference, we proposed a Multi-input Multi-output Forward Regression Orthogonal Least Squares (MFROLS) algorithm for processing multi-input multi-output data to identify the NARX model of the same structural system. …”
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1690
STRUCTURAL-COMPOSITIONAL MODEL OF THE NYURBINSKAYA KIMBERLITE PIPE FORMATION (SREDNE-MARKHA AREA OF THE YAKUTIAN DIAMONDIFEROUS PROVINCE)
Published 2016-09-01“…Analysis of different faults and tectonic fracturing allowed to reconstruct the tectonic stress fields acting at the stage of the kimberlite body formation and to determine their occurrence sequence in time. The data obtained about regularities of the Nyurbinskaya pipe compositional structure and results of geologo-structural studies are combined in a single structural-compositional model of the deposit formation. …”
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1691
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1692
Utility of UAS-LIDAR for estimating forest structural attributes of the Miombo woodlands in Zambia.
Published 2025-01-01“…The estimation of forest structural data in area-based forest inventories relies on the relationship between field-based estimates of forest structural attributes (FSA) and lidar-derived metrics at plot level, which can be modeled using either parametric or non-parametric regression techniques. …”
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1693
Structural Feature-Preserving Point Cloud Denoising Method for Aero-Engine Profile
Published 2022-01-01“…In order to ensure that noise is removed without blurring or distorting structural features, a structural feature-preserving point cloud denoising method is proposed. …”
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1694
Structural Component Identification and Damage Localization of Civil Infrastructure Using Semantic Segmentation
Published 2025-07-01“…The data includes semantic segmentation masks for both categorizing structural elements (slabs, beams, and columns) and assessing structural damage (concrete spalling or exposed rebars). …”
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1695
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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1696
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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1697
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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1698
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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1699
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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1700
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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