All-Weather Precipitable Water Vapor Retrieval over Land Using Integrated Near-Infrared and Microwave Satellite Observations by Shipeng Song, Mengyao Zhu, Zexing Tao, Duanyang Xu, Sunxin Jiao, Wanqing Yang, Huaxuan Wang, Guodong Zhao

“…This study proposes an innovative approach that uses ensemble learning models to integrate infrared and microwave satellite data and other geographic features to achieve all-weather PWV retrieval. …”
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Kolmogorov–Arnold Network in the Fault Diagnosis of Oil-Immersed Power Transformers by Thales W. Cabral, Felippe V. Gomes, Eduardo R. de Lima, José C. S. S. Filho, Luís G. P. Meloni

“…Our work is the first to employ a dedicated KAN in an imbalanced data real-world scenario, named KAN_Diag, while also applying the synthetic minority based on probabilistic distribution (SyMProD) technique for balancing the data in the fault diagnosis. …”
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Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

“…Using demographic, clinical and laboratory data of the patients, six different machine learning algorithms (SVM, KNN, ANN, Decision Tree, Naive Bayes and Discriminant Analysis) were used for classification. …”
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Development and validation of an Arabic tool for assessment of post-vaccination confidence in COVID-19 vaccines (ARAB-VAX-CONF) by Rowan Abuyadek, Samar Abd ElHafeez, Mohamed Mostafa Tahoun, Sally Samir Othman, Abdelrahman Omran, Naglaa Fathy, Ramy Mohamed Ghazy

“…Confirmatory factor analysis confirmed the adequate psychometric properties and fit with observed data (root-mean-square error of approximation = 0.08, comparative fit index = 0.945, Tucker-Lewis index = 0.924, standardized root-mean-square residual = 0.086, normed fit index = 0.918, and goodness-of-fit index = 0.909). …”
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IMERG V07B and V06B: A Comparative Study of Precipitation Estimates Across South America with a Detailed Evaluation of Brazilian Rainfall Patterns by José Roberto Rozante, Gabriela Rozante

“…Over the continent, however, these discrepancies are reduced due to the correction of observations in the final version of IMERG. A comprehensive analysis of the RMSE across Brazil, both as a whole and within the five analyzed regions, without differentiating precipitation classes, demonstrates that version V07B effectively reduces errors compared to version V06B. …”
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Validation of the Brazilian Oral Health Literacy-Adults Questionnaire by Eliete Rodrigues Almeida, Mohammad Mehdi Naghibi Sistani, Cristiane Baccin Bendo, Isabela de Almeida Pordeus, Ramon Targino Firmino, Saul Martins Paiva, Fernanda Morais Ferreira

“…Data were analyzed using SPSS Statistics software and the Mplus program. …”
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A Hybrid RBF-PSO Framework for Real-Time Temperature Field Prediction and Hydration Heat Parameter Inversion in Mass Concrete Structures by Shi Zheng, Lifen Lin, Wufeng Mao, Yanhong Wang, Jinsong Liu, Yili Yuan

“…This study proposes an RBF-PSO hybrid framework for efficient inversion analysis of hydration heat parameters in mass concrete temperature fields, addressing the computational inefficiency and accuracy limitations of traditional methods. …”
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A Wearable Sensor Node for Measuring Air Quality Through Citizen Science Approach: Insights from the SOCIO-BEE Project by Nicole Morresi, Maite Puerta-Beldarrain, Diego López-de-Ipiña, Alex Barco, Oihane Gómez-Carmona, Carlos López-Gomollon, Diego Casado-Mansilla, Maria Kotzagianni, Sara Casaccia, Sergi Udina, Gian Marco Revel

“…PM_2.5 sensor data were validated through two approaches: direct comparison with reference stations and spatial clustering analysis using K-means. …”
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Magnetic particle grinding and finishing test of mixed particle size abrasives by Bingyang LIU, Yunlong DING, Wenjie SHAO, Bing HAN, Yan CHEN

“…In order to simplify the test device, reduce the test cost and improve the processing effect, the single particle size abrasive is changed to mixed particle size abrasive without changing the test device, so as to improve the grinding effect of magnetic particles.MethodsFinite element analysis software is used to simulate the magnetic field in the machining area, and the magnetic field data is imported into the discrete element simulation software through an API interface to obtain the magnetic field during the simulation process, in order to simulate the force situation of mixed particle size abrasive and single particle size abrasive during machining. …”
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A neoteric technique to validate radon-222 transport modelling from a gold mine tailings dam by Frank S. Komati, O. M. Ntwaeaborwa, R. Strydom

“…Model validation from statistical analysis showed a constant trend with minimum variability in the Index of Agreement (IOA), Normalized Mean Square Error (NMSE), and Fraction of Predictions method within a factor of two (FAC2) values. …”
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High-Resolution 3D Geological Modeling of Three-Phase Zone Coexisting Hydrate, Gas, and Brine by Han Yu, Ju Wang, Wei Deng, Zenggui Kuang, Tingwei Li, Zhangshu Lei

“…A comparison between the modeling results and well data indicates a relatively small error margin, offering valuable insights for future development efforts. …”
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Operational Performance Assessment of PV-Powered Street Lighting: A Comparative Study of Different Machine Learning Prediction Models by Safwan Nadweh, Nabil Mohammed, Charalambos Konstantinou, Shehab Ahmed

“…The results indicate that DNNs and DBNs algorithms achieve the lowest error rate (2.5%) and highest accuracy (97%) with high-quality data. …”
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Determination of Spatiotemporal Gait Parameters Using a Smartphone’s IMU in the Pocket: Threshold-Based and Deep Learning Approaches by Seunghee Lee, Changeon Park, Eunho Ha, Jiseon Hong, Sung Hoon Kim, Youngho Kim

“…The proposed method achieved error rates in event detection below 2% of the gait cycle for healthy gait and a maximum of 4.4% for patient gait in event detection, with corresponding parameter estimation errors also within 4%. …”
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SICNN: Soft Interference Cancellation Inspired Neural Network Equalizers by Stefan Baumgartner, Oliver Lang, Mario Huemer

“…In recent years data-driven machine learning approaches have been extensively studied to replace or enhance traditionally model-based processing in digital communication systems. …”
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Actual Truck Arrival Prediction at a Container Terminal with the Truck Appointment System Based on the Long Short-Term Memory and Transformer Model by Mengzhi Ma, Xianglong Li, Houming Fan, Li Qin, Liming Wei

“…The LSTM-Transformer model combines the advantages of LSTM in processing time dependencies and the high efficiency of the transformer in parsing complex data contexts, innovatively addressing the limitations of traditional models when faced with complex data. …”
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Predicting carbon dioxide emissions using deep learning and Ninja metaheuristic optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Ibrahim Elbatal, Ehab M. Almetwally, Marwa M. Eid, El-Sayed M. El-Kenawy

“…Abstract This paper provides a novel approach to estimating CO₂ emissions with high precision using machine learning based on DPRNNs with NiOA. The data preparation used in the present methodology involves sophisticated stages such as Principal Component Analysis (PCA) as well as Blind Source Separation (BSS) to reduce noise as well as to improve feature selection. …”
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Antecedents of Traveller Identification and Satisfaction As a Consequence of Traveller Decisions by Muhammad Aqsa, Aetken Ibrahim, Suparman Parintak, Anne Attas

“…The sample consisted of 100 respondents, with using the margin of error (MOE) formula. The data that has been collected will be subjected to verification and descriptive analysis with statistical tool SmartPLS. …”
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Applying the greenhouse gas inventory calculation approach to predict the forest carbon sink by Fredric Mosley, Jari Niemi, Sampo Soimakallio

“…The tool can replicate forest GHG balances for forest land with an average annual error of 1.0 Mt CO2, representing 4% of the average annual forest carbon sink. …”
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SASTGCN: Semantic-Augmented Spatio-temporal graph convolutional network for subway flow prediction by Shiyuan Jin, Changfeng Jing, Sheng Yao, Yushan Zhang, Pu Zhao, Jinlong Zhang

“…The SASTGCN model was validated with the card swiping data in Shanghai, the prediction ability and error analysis results demonstrated the performance outperform nine baseline methods, and the accuracy was improved by approximately 21%. …”
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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…This research makes a substantial contribution to the application of machine learning in banking, facilitating more accurate data-driven decision-making and more robust risk management practices.…”
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