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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Canopy height mapping in French Guiana using multi-source satellite data and environmental information in a U-Net architecture by Kamel Lahssini, Nicolas Baghdadi, Guerric le Maire, Guerric le Maire, Ibrahim Fayad, Ibrahim Fayad, Ludovic Villard

“…The potential of a U-Net architecture trained on sparse and unevenly distributed GEDI data to generate a continuous canopy height map at a regional scale was assessed. The developed model, named CHNET, successfully produced a canopy height map of French Guiana at a 10-m spatial resolution, achieving relatively good accuracy compared to a validation airborne LiDAR scanning (ALS) dataset. …”
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A hybrid deep learning framework for skin disease localization and classification using wearable sensors by Xiaoling Zhao, Huixin Zhang, Qian Zheng, Caihong Jing

“…This CNN-based multimodal fusion approach improves the model’s ability to capture spatial relationships and enhances classification performance. …”
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Evaluating the Quality of Light Emitted by Smartphone Displays by Nina Piechota, Krzysztof Skarżyński, Kamil Kubiak

“…It covered the color gamut, channel linearity response, refresh rate, flickering, spatial radiation distribution, luminance, uniformity, and static contrast. …”
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Newly established forests dominated global carbon sequestration change induced by land cover conversions by Dailiang Peng, Bing Zhang, Shijun Zheng, Weimin Ju, Jing M. Chen, Philippe Ciais, Huadong Guo, Yuhao Pan, Le Yu, Yidi Xu, Bin Zhao, Jón Atli Benediktsson, Alfredo R. Huete, Zhou Shi, Yueming Hu, Liangyun Liu, Fang Chen, Miaogen Shen, Lei Huang, Xiaoyang Zhang

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Study on interaction mechanism between natural convection and forced convection during storage and temperature rise of waxy crude oil tank by Wei Sun, Yuduo Liu, Wenhua Xu, Lihui Kan, Hongfei Liu, Lixin Zhao, Zhihua Wang

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Integration Of Steam With Constructed Network Media To Improve Mathematics Learning For Class VIII Junior High School Students by Dini Sheila Muflikhah

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The operational medium-range deterministic weather forecasting can be extended beyond a 10-day lead time by Kang Chen, Tao Han, Fenghua Ling, Junchao Gong, Lei Bai, Xinyu Wang, Jing-Jia Luo, Ben Fei, Wenlong Zhang, Xi Chen, Leiming Ma, Tianning Zhang, Rui Su, Yuanzheng Ci, Bin Li, Xiaokang Yang, Wanli Ouyang

“…Abstract Given the complexity of the atmospheric system, current numerical weather prediction models struggle with accurate forecasts. …”
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Meteorological Anomalies During Earthquake Preparation: A Case Study for the 1995 Kobe Earthquake (M = 7.3) Based on Statistical and Machine Learning-Based Analyses by Masashi Hayakawa, Shinji Hirooka, Koichiro Michimoto, Stelios M. Potirakis, Yasuhide Hobara

“…We have utilized a combinational use of NARX (Nonlinear Autoregressive model with eXogenous inputs) and Long Short-Term Memory (LSTM) models, which was successful in objectively re-confirming the anomalies in both parameters on the same day prior to the EQ. …”
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Weapon detection with FMR-CNN and YOLOv8 for enhanced crime prevention and security by Shanthi P, Manjula V

“…Such a combination enables the concurrent utilization of high-resolution spatial context information and rapid frame-wise predictions, thus making it well-suited for continuous video surveillance tasks. …”
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Artificial Intelligence and Objective‐Function Methods Can Identify Bankfull River Channel Extents by Jonathan Garber, Karen Thompson, Matthew J. Burns, Joshphar Kunapo, Geordie Z. Zhang, Kathryn Russell

“…To address this limitation, we developed and tested two automated channel delineation methods that define bankfull according to different conceptualisations of bankfull extent: (a) a cross‐sectional method called HydXS that identifies the elevation which maximizes hydraulic depth (cross‐section area/wetted width); and (b) a neural network image segmentation model based on a pretrained model (ResNet‐18), retrained with images derived from a digital elevation model. …”
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Mechanical Analysis of Mining Stress Transfer on Isolated Island Face in Extra-Thick Fully Mechanized Top-Coal Caving Mining by Min Tu, Qingwei Bu, Baojie Fu, Yu Wang

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Early detection of Zymoseptoria tritici infection on wheat leaves using hyperspectral imaging dataData INRAE by Lorraine Latchoumane, Martin Ecarnot, Ryad Bendoula, Jean-Michel Roger, Silvia Mas-Garcia, Heloïse Villesseche, Flora Tavernier, Maxime Ryckewaert, Nathalie Gorretta, Pierre Roumet, Elsa Ballini

“…These data are valuable since they can be used as a basis to monitor disease's development over time, to build leaf classification models according to their infection status per genotype per day, to develop prediction models related to symptoms' appearance, or to test imaging and spectral analysis methods.…”
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The effects of perfluoroalkyl substance pollution on microbial community and key metabolic pathways in the Pearl River Estuary by Wei Lin, Junlin Zhao, Xingqi Wu, Jiakun Jiang, Chunyang Zhou, Jiating Zheng, Cheng Zhang, Ying Guo, Li Wang, How Yong Ng, Song Li, Shengrui Wang

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The heterogeneity of mortality burden of lower respiratory infection associated with ambient temperature and its drivers in China by Sujuan Chen, Jinlei Qi, Yulin Zhuo, Jianxiong Hu, Jiangmei Liu, Peng Yin, Tao Liu, Mengen Guo, Guanhao He, Ziqiang Lin, Fengrui Jing, Jinling You, Wenjun Ma, Maigeng Zhou

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Extended Kalman filter on sparse identification of nonlinear systems: application to the SoC estimation of a phase change material-based energy storage by Mustapha Habib, Youssef Elomari, Felix Hochwallner, Adam Buruzs, Tilman Barz, Qian Wang

“…Since SoC is not a direct measurement, there is a need for highly accurate prediction models. In this article, we propose solving this challenge by employing sparse identification of nonlinear dynamics (SINDy) to unlock the nonlinear dynamic complexity of PCM-TES. …”
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Individualizing glioma radiotherapy planning by optimization of a data and physics-informed discrete loss by Michal Balcerak, Jonas Weidner, Petr Karnakov, Ivan Ezhov, Sergey Litvinov, Petros Koumoutsakos, Tamaz Amiranashvili, Ray Zirui Zhang, John S. Lowengrub, Igor Yakushev, Benedikt Wiestler, Bjoern Menze

“…We present the Glioma Optimizing the Discrete Loss (GliODIL) framework, which infers the full spatial distribution of tumor cell concentration from available multi-modal imaging, leveraging a Fisher-Kolmogorov type physics model to describe tumor growth. …”
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Seismic Facies Classification of Salt Structures and Sediments in the Northern Gulf of Mexico Using Self-Organizing Maps by Silas Adeoluwa Samuel, Camelia C. Knapp, James H. Knapp

“…While conventional techniques like core analysis and well logs provide limited spatial reservoir information, seismic data can offer valuable 3D insights into fluid and rock properties away from the well. …”
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Integrating Temporal Vegetation and Inundation Dynamics for Elevation Mapping Across the Entire Turbid Estuarine Intertidal Zones Using ICESat-2 and Sentinel-2 Data by Siqi Yao, Jianrong Zhu, Wanying Zhang, Bo Tian, Weiwei Sun, Weiguo Zhang, Weiming Xie, Pengjie Tao, Chunpeng Chen, Kai Tan

“…These two features effectively utilize the variations observed in different regions and land covers within the Sentinel-2 image series caused by the unique tide periodic fluctuation phenomenon and elevation trend law in intertidal zones, thereby rendering the method applicable to elevation prediction across the entire spatial range of intertidal zones, rather than being limited to nonvegetated regions. …”
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Spatiotemporally weighted regression (STWR) for assessing Lyme disease and landscape fragmentation dynamics in Connecticut towns by Zhe Wang, Xiang Que, Meifang Li, Zhuoming Liu, Xun Shi, Xiaogang Ma, Chao Fan, Yan Lin

“…The integration of data-driven and model-driven approaches in this study delivers a robust framework that combines empirical pattern detection with theoretical insight, enhancing the robustness and predictive power of ecological studies.…”
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