Spatial Structure Analysis for Subsurface Defect Detection in Materials Using Active Infrared Thermography and Adaptive Fixed-Rank Kriging by Chun-Han Chang, Stefano Sfarra, Nan-Jung Hsu, Yuan Yao

“…The study focuses on reducing noise and nonstationary backgrounds in data collected through active infrared thermography (AIRT) for defect detection in materials. …”
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Structured-illumination reflectance imaging for the evaluation of microorganism contamination in pork: effects of spectral and imaging features on its prediction performance by Binjing Zhou, Xiaohua Liu, Yan Ge, Kang Tu, Jing Peng, Juan Francisco García-Martín, Jie Wu, Weijie Lan, Leiqing Pan

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Quantitative analysis of EXAFS data sets using deep reinforcement learning by Eun-Suk Jeong, In-Hui Hwang, Sang-Wook Han

“…The deep RL method effectively determined the local structural properties of PtOx and Zn-O complexes by fitting a series of EXAFS data sets to theoretical EXAFS calculations without imposing specific constraints. …”
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MonteCarloSEM: An R Package to Simulate Data for SEM by Fatih Orçan

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Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case by Tirta Wisnu Permana, Gatot Yudoko, Eko Agus Prasetio

“…Specifically, it investigates the relationships among CLIs to forecast Indonesia's Manufacturing Cycle (ManC) using Partial Least Squares-Structural Equation Modeling (PLS-SEM).Building on an extensive literature review, the study employs quarterly data spanning from Q1 2010 to Q2 2022, incorporating five constructs representing key economic sectors influencing the manufacturing cycle. …”
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Editorial: Approaches to improve the performance of virtual screening: scoring functions, structural filtration, prediction of physicochemical properties/pharmacological activity by Hélcio Silva Dos Santos, Hélcio Silva Dos Santos, Hélcio Silva Dos Santos, Alexander Veselovsky, Dmitry Nilov

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Review Condition of Fitness Clubs in Ardabil from the Perspective of Safety and Security by Mohammad Sadeg Ojeh, Nasrin Azizian Kohan

“…Non-structural safety considerations: Ventilation and thermostats-average/Guides and signs-average/Medium light and sound systems/Parking and amenities-weak. …”
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Primary disability of children in the Astrakhan region: analysis of statistical data for 2018-2022 by A. A. Antonova, E. B. Starodubova, A. A. Svetlichkina, S. I. Stepanova, E. O. Bobyr

“…A systematic analysis of primary childhood disability and its structure in the Astrakhan region for 2018-2022 was carried out. …”
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Evaluation of chemical kinetic models for simulations of hydrogen detonations by comparison with experimental data by Vigneshwaran Sankar, Karl P. Chatelain, Deanna A. Lacoste

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Integrated Wavelet-Grey-Neural Network Model for Heritage Structure Settlement Prediction by Yonghong He, Pengwei Jin, Xin Wang, Shaoluo Shen, Jun Ma

“…To address the issue of insufficient prediction accuracy in traditional GM(1,1) models caused by significant nonlinear fluctuations in time-series data for ancient building structural health monitoring, this study proposes a wavelet decomposition-based GM(1,1)-BP neural network coupled prediction model. …”
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Modular Multifunctional Composite Structure for CubeSat Applications: Embedded Battery Prototype Thermal Analysis by Giorgio Capovilla, Enrico Cestino, Leonardo Reyneri, Federico Valpiani

“…Starting from the framework of project ARAMIS (an Italian acronym for a highly modular architecture for satellite infrastructures), a new concept of smart tiles has been developed, employing multifunctional structures and lightweight, composite materials. This enables increased CubeSat mass efficiency and payload volume. …”
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Utility of UAS-LIDAR for estimating forest structural attributes of the Miombo woodlands in Zambia. by Hastings Shamaoma, Paxie W Chirwa, Jules C Zekeng, Abel Ramoelo, Andrew T Hudak, F Handavu, Stephen Syampungani

“…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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Structural Feature-Preserving Point Cloud Denoising Method for Aero-Engine Profile by Jieqiong Yan, Laishui Zhou, Jun Wang, Xiaoping Wang, Xia Liu

“…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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Structural Component Identification and Damage Localization of Civil Infrastructure Using Semantic Segmentation by Piotr Tauzowski, Mariusz Ostrowski, Dominik Bogucki, Piotr Jarosik, Bartłomiej Błachowski

“…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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Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy by Aileen Luo, Tao Zhou, Martin V. Holt, Andrej Singer, Mathew J. Cherukara

“…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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Interpretive Structural Modeling of Factors Affecting Organizational Ambidexterity in the Ministry of Sports and Youth by Ainolah Ahmadnejad Joghie, Mozafar Yektayar, Mozhgan Khodamoradpoor

“…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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Intelligent Identification of Structural Damage Based on the Curvature Mode and Wavelet Analysis Theory by Longsheng Bao, Yue Cao, Xiaowei Zhang

“…Data fitting is then performed to estimate the degree of structural damage. …”
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Predictive modeling of visible-light azo-photoswitches’ properties using structural features by Said Byadi, P. K. Hashim, Pavel Sidorov

“…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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Structural Constraints in Current Stomatal Conductance Models Preclude Accurate Prediction of Evapotranspiration by Pushpendra Raghav, Mukesh Kumar, Yanlan Liu

“…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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Enhancing structural health monitoring with machine learning for accurate prediction of retrofitting effects by A. Presno Vélez, M. Z. Fernández Muñiz, J. L. Fernández Martínez

“…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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