Influence of Aerobic Exercise Load Intensity on Children’s Mental Health by Sihong Zhao

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Open system of text processing for scientometric and bibliometric purposes by L. S. Lomakina, A. S. Surkova, D. V. Zhevnerchuk, O. S. Rassadin

“…The key features of the proposed solution are the ability to implement basic algorithms for text data analyzing and processing in the form of RESTful services, executing of these processes in a distributed processing environment, creating combined algorithms based on them, and also the ability to build an applied programming interface for creating client-server systems with mobile and fixed client subsystems in the field of science and education.…”
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Hybrid Hunger Games Search optimization using a neural networks approach applied to UAVs by Nadia Samantha Zuñiga-Peña, Salatiel Garcia-Nava, Norberto Hernandez-Romero, Juan Carlos Seck-Touh-Mora

“…Optimization methods like population-based algorithms are valuable when applied to multidimensional and nonlinear problems. …”
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Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues by Gianmarco Lazzini, Mario D’Acunto

“…In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. …”
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An end-to-end real-time pollutants spilling recognition in wastewater based on the IoT-ready SENSIPLUS platform by Luca Gerevini, Gianni Cerro, Alessandro Bria, Claudio Marrocco, Luigi Ferrigno, Michele Vitelli, Andrea Ria, Mario Molinara

“…The data processing is based on a commercial Micro Control Unit (MCU), including an anomaly detection module, a classification module, and a false positive reduction module, all based on machine learning algorithms that have a computational complexity suitable for low-cost hardware implementation.An extensive experimental campaign on different contaminants has been carried out to train machine-learning algorithms suitable for low-cost and low-power MCU. …”
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A data-driven approach to solve the RT scheduling problem by Mruga Gurjar, Jesper Lindberg, Thomas Björk-Eriksson, Caroline Olsson

“…The comparison between manual and algorithm allocations showed that the number of delayed patients reduced by 10 % in the algorithm suggestion with an average delay reduction of 2 weeks. …”
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Unbiased High-Precision Cloud Detection for Advanced Himawari Imager Using Automatic Machine Learning by Bochun Liu, Jinming Ge, Qingyu Mu, Chi Zhang, Xiaoyu Hu, Jiajing Du, Yanyan Wu, Bo Wang, Xiang Li, Jianping Huang, Qiang Fu

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Early Warning of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Multi-Omics Signature: A Machine Learning-Based Retrospective Study by Ke Z, Shen L, Shao J

“…The AUC of GLRM was 0.818 (95% CI: 0.757~0.879), significantly lower than that of RFM’s AUC 0.893 (95% CI: 0.836~0.950).Conclusion: The prediction models based on machine learning (ML) algorithms and multiomics have shown good performance in predicting ALN metastasis, and RFM shows greater advantages compared to traditional GLRM. …”
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Towards a Digital Twin for Gas Turbines: Thermodynamic Modeling, Critical Parameter Estimation, and Performance Optimization Using PINN and PSO by Jian Tiong Lim, Achnaf Habibullah, Eddie Yin Kwee Ng

“…The results demonstrated that GTPO could be optimized with the application of conformal prediction when the true GTPO is detected to be higher than the upper range of GTPO obtained from the ANN model with a conformal prediction of a 95% confidence level. …”
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Method and Optimization of Key Parameters of Soil Organic Matter Detection Based on Pyrolysis Coupled with Artificial Olfaction by Mingwei Li, Xiao Li, Xuexun Li, Wenjun Wang, Yulong Chen, Long Zhou, Xiaomeng Xia

“…Finally, the Back-Propagation Neural Network (BPNN) and Partial Least-Squares Regression (PLSR) algorithms were used to establish an SOM prediction model after obtaining soil pyrolysis gases under the optimal combination of pyrolysis parameters. …”
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Leveraging AI to explore structural contexts of post-translational modifications in drug binding by Kirill E. Medvedev, R. Dustin Schaeffer, Nick V. Grishin

“…Recent advancements in computational power and artificial intelligence, particularly in deep learning algorithms and protein structure prediction tools like AlphaFold3, have opened new possibilities for exploring the structural context of interactions between PTMs and drugs. …”
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Development and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study by Jiexin Chen, Qiongbing Zheng, Youmian Lan, Meijing Li, Ling Lin

“…LASSO regression, XGBoost algorithm, and RF algorithm were used to identify significant indicators, and a OA prediction nomogram was developed. …”
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Embedding With Preservation of Semantics of the Original Data by M. E. Vatkin, D. A. Vorobey, M. V. Yakovlev, M. G. Krivova

“…Working with them can be computationally inefficient, and often leads to overfitting; therefore, the data dimension reduction algorithms are used, one of which is auto encoders. …”
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Development of an Intelligent Method for Target Tracking in Radar Systems at the Initial Stage of Operation Under Intentional Jamming Conditions by Serhii Semenov, Olga Wasiuta, Alla Jammine, Justyna Golec, Magdalena Krupska-Klimczak, Yevhen Tarasenko, Vitalii Voronets, Vitalii Breslavets, Serhii Lvov, Artem Moskalenko

“…The dynamic weighting algorithm between model estimates ensures a balance between accuracy and robustness. …”
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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…The thematic analysis revealed five major categories: 1. Prediction of exclusive breastfeeding patterns: AI models, such as decision trees and machine learning algorithms, identify factors influencing breastfeeding practices, including maternal experience, hospital policies, and social determinants, highlighting actionable predictors for intervention. 2. …”
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Smart photonic wristband for pulse wave monitoring by Renfei Kuang, Zhuo Wang, Lin Ma, Heng Wang, Qingming Chen, Arnaldo Leal Junior, Santosh Kumar, Xiaoli Li, Carlos Marques, Rui Min

“…Several different speckle pattern processing algorithms and POFs with different core diameters were evaluated. …”
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Graph semantic similarity-based automatic assessment for programming exercises by Chengguan Xiang, Ying Wang, Qiyun Zhou, Zhen Yu

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PLL-VO： An Efficient and Robust Visual Odometry Integrating Point-Line Features and Neural Networks by L. Zhao, Y. Yang, D. Ma, X. Lin, W. Wang

“…PLL-VO system are evaluated in multiple datasets under various lighting conditions, demonstrating a 6.3% reduction in absolute trajectory error for pose estimation compared to state-of-the-art (SOTA) algorithms, the average computation time for visual odometry (43 ms) shows a 29.74% decrease compared to the state-of-the-art (SOTA) algorithms.…”
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An AIoT Architecture for Structural Testing: Application to a Real Aerospace Component (Embraer E2 Model Aircraft Flag Track) by Pablo Venegas, Unai Virto, Isidro Calvo, Oscar Barambones

“…In order to illustrate the integration of different AI techniques in the AIoT architecture, ARIMA and LSTM algorithms were used to analyze the data captured with three sensors. …”
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Image Super Resolution Reconstruction Based on Multi-Level Residual Skip Connection Network by WANG Xiaoyu, LU Jianyu, WEI Yuxin, YU Yue

“…Compared with other commonly used super-resolution algorithms, this algorithm can better retain texture details during image reconstruction, resulting in clearer image details, better visual effects and effective reduction of the number of parameters in the network. …”
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