Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods by Amin Shabani Ammari, Younes Nouri, Habib Ghasemi Jouneghani, Seyed Amin Hosseini, Arash Rayegani, Mehrdad Ebrahimi, Pooria Heydari

“…The ML prediction showed that the CatBoost algorithm had the highest accuracy, with an R2 score of 0.954. …”
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Reliability of interitem signals identification in cross-correlation passive radars by A. A. Dmitrenko, S. Yu. Sedushev

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MOBILE WEB-APPLICATION ARCHITECTURE CONCEPT FOR VIBRATIONAL SIGNALS PROCESSING by V. E. Bazarevsky

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ANALYSIS OF DECODERS BIT ERROR FOR RIJNDAEL And BCH codes by D. M. Bildziuk, S. B. Salomatin

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CORRECTION commute decoder for Multiple Errors WITH not primitive BCH-codes by V. A. Lipnitski, A. O. Aliaksiuk

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VIDEO SCRAMBLING by N. A. Laurynovich

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HARDWARE-SOFTWARE COMPLEX OF EXPRESS DIAGNOSTICS OF PSYCHO PHYSIOLOGICAL INDICATORS OF THE HUMAN BODY by N. L. Bobrova

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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…In outdoor field experiments conducted under cloudy, low-light, and artificial lighting conditions, the model achieved localization errors of 2.43 mm (X-axis), 3.70 mm (Y-axis), and 1.28 mm (Z-axis), representing reductions of 19.27 %, 12.67 %, and 23.05 %, respectively. …”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…Cox models showed consistent reductions in 30-day (HR = 0.199, 95% CI: 0.124–0.320, p < 0.001) and 90-day (HR = 0.230, 95% CI: 0.150–0.352, p < 0.001) mortality. …”
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Time-delayed vibration control and parameter optimization of semi-active vehicle suspension designed for random road excitation by Yong Guo, Yong-Jing Li, Yan-Bo Wei

“…Under the influence of road excitations, the acquisition of optimal time-delayed feedback control parameters is deemed crucial for the improvement of the vibration reduction effect of semi-active vehicle suspension systems. …”
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Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer by Peng Zhang, Meizhong Qin, Fen Li, Kunpeng Hu, He Huang, Cuicui Li

“…Most existing models rely on single-omics data and limited algorithms, reducing robustness and clinical value. …”
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Improving fluoroprobe sensor performance through machine learning by D. Lafer, A. Sukenik, T. Zohary, O. Tal

“…Phytoplankton species biomass data were collected concurrently using standard inverted microscope counts. The SVR algorithm outperformed the other algorithms in predicting phytoplankton abundance and composition in Lake Kinneret, based on the FP measurements. …”
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MolNexTR: a generalized deep learning model for molecular image recognition by Yufan Chen, Ching Ting Leung, Yong Huang, Jianwei Sun, Hao Chen, Hanyu Gao

“…In addition, it employs a series of novel augmentation algorithms to significantly enhance the robustness and performance of the model.…”
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Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays by Sina Hasibi Taheri, Javad Mohammadpour, Ali Lalbakhsh, Slawomir Koziel, Stanislaw Szczepanski

“…Decision Tree-based models are chosen to provide accurate prediction while minimizing the dataset preparation time. …”
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Artificial intelligence for children with attention deficit/hyperactivity disorder: a scoping review by Bo Sun, Bo Sun, Fei Cai, Huiman Huang, Bo Li, Bing Wei

“…Artificial intelligence provides advanced models and algorithms for better diagnosis, prediction and classification of attention deficit/hyperactivity disorder. …”
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Personalizing the Marketing with Artificial Intelligence (AI) by Rozhko Viktor I., Pletnova Yelyzaveta S.

“…Another major challenge is the technical limitations of AI. While AI algorithms are capable of analyzing vast amounts of data, they cannot always properly adapt to a changing market environment or predict consumer behavior in non-standard situations. …”
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Use of four next-generation sequencing platforms to determine HIV-1 coreceptor tropism. by John Archer, Jan Weber, Kenneth Henry, Dane Winner, Richard Gibson, Lawrence Lee, Ellen Paxinos, Eric J Arts, David L Robertson, Larry Mimms, Miguel E Quiñones-Mateu

“…In this study, HIV-1 co-receptor usage was predicted for twelve patients scheduled to start a maraviroc-based antiretroviral regimen. …”
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Research on the Evaluation of the Node Cities of China Railway Express Based on Machine Learning by Chenglin Ma, Mengwei Zhou, Wenchao Kang, Haolong Wang, Jiajia Feng

“…The Random Forest model outperformed comparative algorithms with 99.5% prediction accuracy (8.33% higher than conventional classification models), particularly in handling multi-dimensional interactions between urban development factors. …”
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Machine learning in stream and river water temperature modeling: a review and metrics for evaluation by C. R. Corona, T. S. Hogue, T. S. Hogue

“…The aim of this work is threefold: first, to provide a concise review of the use of ML algorithms in SWT modeling and prediction; second, to review ML performance evaluation metrics as they pertain to SWT modeling and prediction to find the commonly used metrics and suggest guidelines for easier comparison of ML performance across SWT studies; and, third, to examine how ML use in SWT modeling has enhanced our understanding of spatial and temporal patterns of SWT and examine where progress is still needed.…”
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Machine Learning (ML) Based Repair-Count and Periodic Maintenance Policy for Multipurpose CNC Machinery by Alifin Fakhri Ikhwanul, Winarno, Fasa Nadia, Darajatun Rizki Achmad, Kusnadi, Safariyani Eva

“…Several censored data were utilized to predict failure times using machine learning algorithms, such as process temperature, air temperature, rotational speed, and torque. …”
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