Time resolution of wind speed data introduces errors in wind power density assessment by Xinrong Yang, Yiheng Tao, Yubin Jin, Bin Ye, Fan Ye, Weili Duan, Rongrong Xu, Zhenzhong Zeng

“…Through analysis of wind speed data at nine resolutions, ranging from 10-minute to monthly intervals, we uncover significant errors introduced by coarser time resolutions in WPD calculations. …”
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Pine Wilt Disease Monitoring Using Multimodal Remote Sensing Data and Feature Classification by Xin Ye, Hanwen Yu, Yan Yan, Tieming Liu, Yan Zhang, Taoli Yang

“…To facilitate practical implementation, we developed a deep learning-based model, PWD-Net, which efficiently integrates these multimodal data for the monitoring of diseased pine trees. …”
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Inferring mobility of care travel behavior from transit smart fare card data by Awad Abdelhalim, Daniela Shuman, Anson F. Stewart, Kayleigh B. Campbell, Mira Patel, Gabriel L. Pincus, Inés Sánchez de Madariaga, Jinhua Zhao

“…In contrast to past studies that have quantified the impact of gender using survey and qualitative data, we examine a novel data-driven workflow utilizing a combination of previously developed origin, destination, and transfer inference (ODX) based on individual transit fare card transactions, name-based gender inference, and geospatial analysis as a framework to identify mobility of care trip making. …”
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State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach by Sesidhar Dvsr, Chandrashekhar Badachi, Chandrashekar Nagawaram, Panduranga Chary Kondoju, C. Dhanamjayulu, Innocent Kamwa

“…The present work investigates the estimation of state of charge (SoC) of Lithium Ion (Li-ion) batteries focussing on data-driven methodologies developed during the last five years. …”
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The correlation of acoustic and morphometric parameters of the optic nerve and anthropometric data in healthy young people by V. V. Neroev, T. N. Kiseleva, A. V. Baeva, E. K. Eliseeva, A. N. Zhuravleva, A. I. Ushakov, K. V. Lugovkina, T. V. Sudovskaya, I. V. Myshko

“…Studying the acoustic and morphometric characteristics of the intraocular and intraorbital parts of the ON in healthy young people, which included anthropometric data and gender characteristics, will contribute to the development more accurate diagnostic criteria of ON state evaluations.…”
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Hypersensitivity pneumonitis in a child (observational data for six years): A clinical case by V. S. Chulkov, L. V. Medvedeva, E. E. Minina, E. V. Fastakovskaya

“…A clear improvement in clinical, laboratory, and instrumental data was demonstrated over the observation period, with significant effects achieved within a year from the start of therapy. …”
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A comprehensive diagnostic framework for hepatitis C using structured data and predictive analytics by Behnaz Motamedi, Balázs Villányi

“…To test this theory, we established an extensive four-phase preparation pipeline: Baseline imputes missing values using class-specific means; Refine mitigates outliers through class-specific medians and normalization; Balanced addresses class imbalance across five stages employing localized random affine shadow-sampling; and Augmented incorporates a clustering-based feature derived from an ensemble of K-means and Gaussian mixture models, combined with principal component analysis. The prediction model was developed by optimizing feature selection with the ReliefF approach and a random forest classifier employing random search. …”
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Assessing data and sample complexity in unmanned aerial vehicle imagery for agricultural pattern classification by Linara Arslanova, Sören Hese, Marcel Fölsch, Friedemann Scheibler, Christiane Schmullius

“…The study investigates the data and sample complexity required to develop an effective machine/deep learning (ML/DL) model, using techniques such as the Jeffries-Matusita Distance for assessment of class separability and feature importance ranking for feature and layer selection, semivariogram analysis for determining minimum sample patch sizes.The results demonstrate distinct classification capabilities based on spectral information in differentiating between sub-classes such as weed infestation, bare soil, disturbed canopy areas, and undisturbed canopy areas. …”
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Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…This study presents a comprehensive workflow for post-fire forest monitoring using UAV imagery, covering data acquisition, co-alignment, tree segmentation, species classification, and biophysical parameter estimation using growth models. …”
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Research on Coordinated Development of a Railway Freight Collection and Distribution System Based on an “Entropy-TOPSIS Coupling Development Degree Model” Integrated with Machine L... by Yun Jing, Si-Ye Guo, Xuan Wang, Fang-Qiu Chen

“…This paper combines the theories of the integration of collection and distribution theory, coordination theory, and coupling theory and incorporates the machine learning fuzzy mathematics to construct an “Entropy-TOPSIS Coupling Development Degree Model” for dynamic intelligent quantitative analysis of the synergy of railway freight collection and distribution systems. …”
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The T-DBSCAN Algorithm for Stopover Site Identification of Migration Birds Based on Satellite Positioning Data by Xinwu He, Xiqun Liu, Jiajia Liu, Youwen Li, Zhenggang Xu, Ping Mo, Tian Huang

“…However, satellite data are usually characterized by discontinuity, extensive periods, and inconsistent frequency, which challenges cluster analysis. …”
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Integration of UAV Multi-Source Data for Accurate Plant Height and SPAD Estimation in Peanut by Ning He, Bo Chen, Xianju Lu, Bo Bai, Jiangchuan Fan, Yongjiang Zhang, Guowei Li, Xinyu Guo

“…As a globally strategic oilseed crop, peanut plays a vital role in ensuring food and edible oil security. This study aimed to develop an optimized estimation framework for peanut plant height and SPAD values through machine learning-driven integration of UAV multi-source data while evaluating model generalizability across temporal and spatial domains. …”
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From STEM-EDXS data to phase separation and quantification using physics-guided NMF by Adrien Teurtrie, Nathanaël Perraudin, Thomas Holvoet, Hui Chen, Duncan T L Alexander, Guillaume Obozinski, Cécile Hébert

“…This work is implemented within two open-source Python packages, espm and emtables , which are used here for data simulation, data analysis and quantification. …”
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Robust confinement state classification with uncertainty quantification through ensembled data-driven methods by Yoeri Poels, Cristina Venturini, Alessandro Pau, Olivier Sauter, Vlado Menkovski, the TCV Team, the WPTE Team

“…We propose ensembling data-driven methods on two axes: model formulations and feature sets. …”
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Evaluating the completeness of electronic health records in dental education: a big data study by Tamanna Tiwari, Maxim Kondratenko, Nihmath Nasiha, Toan Ong, Sangeetha Chandrasekaran, Gary Kostbade, Zachary Giano

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Features of the clinical course and treatment of anaphylaxis in children in the Ryazan region according to survey data by E. V. Stezhkina, N. A. Belykh, A. I. Agapova, D. I. Suleymanova, A. N. Belyaeva

“…Epidemiological studies on anaphylaxis in the Russian Federation are isolated, so the assessment of data from each region is relevant.Objective: to study the clinical features and medical care for anaphylaxis in children of the Ryazan region in real clinical practice.Materials and methods: A retrospective analysis of medical documentation was carried out in 300 children who had suffered an “acute allergic reaction” over the past 5 years, followed by a telephone survey of patients’ parents about the disease, and based on the clinical criteria for the diagnosis of anaphylaxis presented by the World Organization of Allergists (WAO) in 2020 and in the Federal Clinical Guidelines for the Diagnosis and Treatment of anaphylaxis, 57 patients were selected for anaphylactic shock of the Russian Federation in 2022, whose data were compared in a spreadsheet and analyzed using SPSS V24.0, including descriptive statistics.Results: It was revealed that the average age of first—time anaphylaxis is 3.5 years. …”
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Comparison of water surface temperature retrieval methods from Landsat 9 satellite data by M. Bonansea, M. Bonansea, S. Gutierrez, M. Correa, S. Pana, V. Gauto, F. Nemiña, A. Germán, G. Beltramone, L. Pinotti, L. Pinotti, A. Ferral

“…Landsat 9, the latest satellite in the Landsat program, offers a unique opportunity for retrieving Earth's surface temperature data. Despite numerous efforts to develop methods for retrieving surface temperature from remote sensing data, there have been relatively few studies comparing the performance of these methods. …”
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A data-driven framework for assessing climatic impact drivers in the context of food security by M. R. Benso, R. F. Silva, G. Chiquito Gesualdo, G. Chiquito Gesualdo, A. M. Saraiva, A. C. B. Delbem, P. A. A. Marques, J. A. Marengo, J. A. Marengo, J. A. Marengo, E. M. Mendiondo

“…Data-driven methods can bridge this gap; however, more development must be done to create interpretable models, emphasizing regions lacking data availability. …”
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Industrial data-driven machine learning soft sensing for optimal operation of etching tools by Feiyang Ou, Henrik Wang, Chao Zhang, Matthew Tom, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…For PASS/FAIL classification, a data aggregation method is developed to enhance model predictive performance with larger training datasets. …”
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Thrombolytic Therapy in Treatment in Patients with Pulmonary Embolism not High-risk: SIRENA Registry Data by N. A. Cherepanova, I. S. Mullova, T. V. Pavlova, A. D. Erlikh, O. L. Barbarash, S. A. Berns, E. A. Schmidt, D. V. Duplyakov

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