Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…ObjectiveStructural parameter identification based on swarm intelligent optimization methods has become one of the popular methods for finite element model modification. …”
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Structural Characteristics of the Turning End of the Kaiping Syncline and Its Influence on Coal Mine Gas by Zhenning Chen, Yanming Zhu, Hanyu Zhang, Jin Li

“…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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Damage detection in a reinforced concrete bridge applying wavelet transform in experimental and numerical data by Ramon S. Y. R. C. Silva, Erwin U. L. Palechor, Luciano M. Bezerra, Marcus V. G. de Morais, Welington V. da Silva

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Sociological Analysis of Divorce in Kurdistan Province: Secondary Analysis of Available Data: from 2006 to 2016) by Yaghou Ahmadi, Mehdi Ghaderi

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Damage detection in a reinforced concrete bridge applying wavelet transform in experimental and numerical data by ramon saleno yure rubim costa silva, Erwin U. L. Palechor, Luciano M. Bezerra, Marcus V. G. de Morais, Welington V. da Silva

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Damage Detection in Beam Structures Based on Frequency-Domain Analysis Methods for Nonlinear Systems by Wenbo Zhang, Xiaoyue Guo, Liangliang Cheng, Bo Zhang

“…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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A large-scale dataset of AI-related tweets: Structure and descriptive statisticsGitHubDataverse by Nathalie de Marcellis-Warin, Daniel Kouloukoui, Thierry Warin

“…The final dataset includes structured metadata such as media elements (images, videos, and URLs), user engagement metrics (likes, retweets, replies), hashtags, language codes, and temporal indicators (hour and weekday of posting). …”
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Graph Neural Networks for Analyzing Trauma-Related Brain Structure in Children and Adolescents: A Pilot Study by Harim Jeong, Minjoo Kang, Shanon McLeay, R. J. R. Blair, Unsun Chung, Soonjo Hwang

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NMR Data Analysis of Acarbose by LI Yujiang, ZHAO Wei, TAO Le, LU Bohua, ZHENG Guo, ZHANG Haiyan, GUO Xiaohe, ZHAO Tianzeng

“…The molecular structure of acarbose was confirmed, providing a reliable data basis for the safety and quality control of acarbose drugs.…”
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Reconstructing missing data of damaged buildings from post-hurricane reconnaissance data using XGBoost by Hyunje Yang, Jun-Whan Lee, Steven Klepac, Armando Ulises Santos Cruz, Arthriya Subgranon, Junfeng Jiao

“…For each region, we analyzed the model’s performance depending on the missing structural features. We also demonstrated the importance of including geospatial, hazard, and damage level data by showing improved performance of XGBoost models compared to those trained only on known structural data. …”
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Dataset for evaluation and numerical modelling of structural performance of fibre-reinforced shotcrete with fibres of steel, synthetic and basaltMendeley Data by Andreas Sjölander, Erik Nordström, Anders Ansell

“…This could be used to get an indication of the required dosage of each fibre type to fulfil structural requirements. The raw data from the test machine is valuable for the numerical modelling of fibre-reinforced shotcrete. …”
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Modeling of potential field data for detecting structural and tectonic framework of Esh El Mellaha area, Red Sea, Egypt by Abdelbaset M. Abudeif, Zakaria Hamimi, Gaber M. Gaber, Adel Kotb, Nasir Alarifi, Stefano Bellucci, Marwa M. Masoud

“…To achieve this goal, Bouguer gravity and aeromagnetic data were used, processed and analyzed. Various depth estimation techniques were employed to analyze subsurface structures, each offering distinct advantages. …”
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Structural deformation in central Cuba and implications for the petroleum system: new insights from 3D inversion of gravity data by José Alberto Batista-Rodríguez, Marco Antonio Pérez-Flores, Jesús Blanco-Moreno, Luis Fernando Camacho-Ortegón

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Express Analysis of the Structural and Electronic Properties of Nanomaterials Using Big Data, Large Language Models and Generative Artificial Intelligence by N. A. Shymanski, A. V. Baglov, Kh. B. Musaev, O. N. Ruzimuradov, L. S. Khoroshko

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Empirical Investigation of the Effects of the Measurement-Data Size on the Bayesian Structural Model Updating of a High-Speed Railway Bridge by Kodai Matsuoka, Haruki Yotsui, Kiyoyuki Kaito

“…Bayesian structural model updating (SMU) is among the most powerful methods for estimating the bending stiffness and modal damping of high-speed railway (HSR) bridges and predicting their bridge-response-based resonance responses. …”
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Characterizing forest structural changes in response to non-stand replacing disturbances using bitemporal airborne laser scanning data by Tommaso Trotto, Nicholas C. Coops, Alexis Achim, Sarah E. Gergel, Dominik Roeser

“…These findings showed the potential of bitemporal ALS data in characterizing structural changes due to ESB infestations at fine scale based on canopy cover and height, relevant for forest management strategies to better target current and future infestations.…”
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Sensitivity to change of structural outcomes in axial spondyloarthritis after 10 years of follow up. Data from the DESIR cohort by Sofia Ramiro, Maxime Dougados, Anna Molto, Clementina López-Medina, Alexandre Sepriano, Anne Tournadre

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Analysis of the structural integrity of a frozen wall during a mine shaft excavation using temperature monitoring data by Lev Levin, Mikhail Semin, Ivan Golovatyi

“…The obtained dependencies of the maximum external load on the FW can be used to optimize the operation mode of the freezing station at the ice holding stage (or passive freezing) to increase the energy efficiency of the system and ensure the structural integrity of the FW.…”
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Structural Condition Assessment and Temperature Effect Analysis of Cable–Pylon Anchorage Zone Using Long-Term SHM Data by Hanhui Ye, Zhijian Chen

“…Based on long-term structural health monitoring data, the signals were decomposed and reconstructed at multiple time scales, confirming temperature to be the main factor causing the stress change in the anchorage zone. …”
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Tendon Anomaly Identification in Prestressed Concrete Beams Based on an Advanced Monitoring MEMS and Data-Driven Detection of Structural Damage by Giorgio de Alteriis, Giulio Mariniello, Tommaso Pastore, Alessia Teresa Silvestri, Giuseppe Augugliaro, Ida Papallo, Canio Mennuti, Antonio Bilotta, Rosario Schiano Lo Moriello, Domenico Asprone

“…The integration of MEMS sensors into structural health monitoring (SHM) systems offers a promising approach to long-term structural maintenance, especially in large-scale infrastructure. …”
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