Seismic Vulnerability Assessment of Reinforced Concrete Educational Buildings Using Machine Learning Algorithm by Tapan Kumar, Mohammad Al Amin Siddique, Raquib Ahsan

“…The main objective of this paper is to assess the vulnerability of reinforced concrete (RC) educational buildings in Dhaka city to seismic activity by utilizing machine learning (ML) algorithms. There are three main stages in traditional seismic vulnerability assessment: rapid visual assessment (RVA), preliminary engineering assessment (PEA), and detailed engineering assessment (DEA). …”
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Study results in curvilinear motion of high-speed track machine with electromechanical transmission by V. N. Kuznetsova, R. V. Romanenko

“…The studies in the VISSIM programming environment using typical motion cycles that equivalently reflect the operating conditions and use of a tracked machine were carried out.Results. As a result of the research, quantitative estimates of the influence of the power of a diesel generator and the charge of an energy storage device on the dynamic performance of equipment were obtained. …”
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Using Segmentation to Boost Classification Performance and Explainability in CapsNets by Dominik Vranay, Maroš Hliboký, László Kovács, Peter Sinčák

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Prediction rotary drilling penetration rate in lateritic soils using machine learning models by Eugène Gatchouessi Kamdem, Franck Ferry Kamgue Tiam, Luc Leroy Mambou Ngueyep, Olivier Wounabaissa, Hugues Richard Lembo Nnomo, Abraham Kanmogne

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Ensemble machine learning-based extrapolation of Penman-Monteith-Leuning evapotranspiration data by Vahid Nourani, Ramin Ahmadi, Yongqiang Zhang, Dominika Dąbrowska

“…Sensitivity analysis was performed to optimize the input variables and reduce uncertainty. …”
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Application of a Supervised Learning Machine for Accurate Prognostication of Hydrogen Contents of Bio-Oil by Binghui Xu, Tzu-Chia Chen, Danial Ahangari, S. M. Alizadeh, Marischa Elveny, Jeren Makhdoumi

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Servo System Control of Turntable Lipstick-Filling Machine Based on Particle Swarm Optimization by Xiangqiang Zhong, Wenbo Tao, Lingling Zou, Huaian Yang, Shunyu Yao

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AGE AND GENDER CLASSIFICATION FROM IRIS IMAGES OF THE EYE USING MACHINE LEARNING TECHNIQUES by Martins E. Irhebhude, Adeola O. Kolawole, Halima Abemi

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Satellite imagery pre-processing and feature extraction for the mapping of coastal ecosystems using Google Earth Engine: A workflow for practitioners by Ahmad Badruzzaman, Prawesti Wulandari, Sainal Sainal, Matthew Ashley, Susan Jobling, Melanie C. Austen, Radisti A. Praptiwi

“…This study develops general methodological steps to perform those processes that can be adapted to different management needs. …”
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Predictive Torque Control of Three Phase Axial Flux Permanent Magnet Synchronous Machines by Mohsen Siami, S. Asghar Gholamian

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Evaluation of the Pile Group Response for Machine Foundation under Cyclic Load in Sandy Soil by Saif S. Abd Al-hafiz, Jasim Abbas

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Condition Assessment of the Conical Surface of Atomizer Needles and Seats of Marine Diesel Engines by Acoustic Emission – Preliminary Research by Zygmunt RAUNMIAGI

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An Analysis of Image Classification Using Wavelet-Based Autoencoder Architecture and Extreme Learning Machine by Salwa Said, Salima Hassairi, Siwar Yahia, Ridha Ejbali, Mourad Zaied

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Prediction of sewage pipeline construction duration by introducing machine learning and deep learning approaches by Sang-Jun Park, Norhane Nour, Kang Young Lee, Ju-Hyung Kim

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COVID-19 detection using machine learning and fusion-based deep learning models by Fatima Raheem, Manaf K. Hussein

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Predictive modeling of longitudinal cracking in CRCP using PSO-tuned gradient boosting machines by Ali Alnaqbi, Ghazi G. Al-Khateeb, Waleed Zeiada

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Dispersant for Reducing Mud Cakes of Slurry Shield Tunnel Boring Machine in Sticky Ground by Shisen Zhao, Shuchen Li, Zeen Wan, Manling Wang

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A Machine Learning Approach for the Clustering and Classification of Geothermal Reservoirs in the Ying-Qiong Basin by Yujing Duan, Yuan Liang, Qingyun Ji, Zhong Wang

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Calculation parameter correction of steel truss nodal plate based on machine learning theory by Zhe Hu, Rui Rao, Hao Chen, Qinhe Li, Ronghui Wang

“…The reliability of these two machine learning methods was confirmed through mutual validation, with results showing that the ANN produced more accurate rigid arm length coefficients, while the Bayesian decision tree performed slightly less well. …”
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Machine Learning-Based Empirical Formulations for Strength Properties of Steel Fiber Reinforced Concrete by Mohammad Hossein Taghavi Parsa, Mohammad Reza Adlparvar, Morteza Esmaeili

“…The formulations are presented for flat, waved, and hooked end fibers, the most common fibers used in construction engineering. The machine learning-driven formulations are exclusive due to the utilized strategy and the resources, and the precision of the relations are denoted, which presents the superiority to traditional methods.…”
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