Single-Shot Femtosecond Raster-Framing Imaging with High Spatio-Temporal Resolution Using Wavelength/Polarization Time Coding by Yang Yang, Yongle Zhu, Xuanke Zeng, Dong He, Li Gu, Zhijian Wang, Jingzhen Li

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Research on Multi-Scale Spatio-Temporal Graph Convolutional Human Behavior Recognition Method Incorporating Multi-Granularity Features by Yulin Wang, Tao Song, Yichen Yang, Zheng Hong

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Back-propagation-assisted inverse design of structured light fields for given profiles of optical force by Zhao Xiaoshu, Lin Haoze, Chen Huajin, Zheng Hongxia, Ng Jack

“…Designing a monochromatic spatially-structured light field that recovers the pre-specified profile of optical force (OF) exerted on a particle is an inverse problem. …”
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A novel ensemble learning algorithm integrating WRF-CMAQ and downscaling models for hourly estimation of regional air pollution along with vegetation exposure risk detection by Peng Zhou, Jieming Chou, Shan Ye, Leiku Yang, Mengting Sun, Pengao Li, Huanpeng Wang, Jie Luo, Zhaoxiang Cao, Qian Yao, Hao Zhang, Hongze Pei

“…To achieve this, an integrated machine learning algorithm was developed by coupling the Weather Research and Forecasting-Community Multiscale Air Quality model with a downscaling model to estimate air pollutants during compound pollution episodes in Beijing. …”
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Development and Testing of a Methodology for Assessing of the Correlation Velocity Measurements’ Accuracy for the Hydrodynamic Investigations of the Turbulent Coolant Flow in Nucle... by I. A. Konovalov, A. A. Chesnokov, A. A. Barinov, S. M. Dmitriev, A. E. Khrobostov, M. A. Legchanov, S. S. Borodin, M. A. Makarov

“…Turbulent pulsations at the interface between two concurrent isokinetic flows in a channel with a square cross section are used as the signal source for the correlational algorithm.Paper presents the values of  the  turbulence′s  transport  time  between  spatial  conductometers, the results of estimating the spectral power density and band of the recorded signal and also the signalto-noise ratios of the measuring system obtained on their basis which are subsequently used to estimate the confidence interval of the transport time.As a result of measurements the relationship between the confidence  interval  value  and  the signal length were obtained. …”
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Estimating River Discharge With Swath Altimetry: A Proof of Concept Using AirSWOT Observations by S. Tuozzolo, G. Lind, B. Overstreet, J. Mangano, M. Fonstad, M. Hagemann, R. P. M. Frasson, K. Larnier, P.‐A. Garambois, J. Monnier, M. Durand

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A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns by Irene Biliani, Ekaterini Skamnia, Polychronis Economou, Ierotheos Zacharias

“…Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. …”
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Design of a TSR-based project learning strategy for biochemistry undergraduate teaching and research labs: a case study by Camille R. Reaux, Shelby A. Meche, Jordan M. Grider, Soundharya Dhanabal, Tarikul I. Milon, Feng Chen, Wu Xu

“…A project-oriented learning approach based on the Triangular Spatial Relationship (TSR) algorithm has been developed. …”
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Sentinel-2 Masking CNNs Trained on Physics-Supervised Labels by Efrain Padilla-Zepeda, Kevin Alonso, Raquel De Los Reyes, Deni Torres-Roman, Avi Putri Pertiwi, Tobias Storch

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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

“…This study provides a comprehensive overview of the progress made in applying advanced ML algorithms to assess and monitor GDEs. It begins with a systematic literature review following the PRISMA framework, followed by an analysis of temporal and geographic trends in ML applications for GDE research. …”
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An Efficient and Low-Complexity Transformer-Based Deep Learning Framework for High-Dynamic-Range Image Reconstruction by Josue Lopez-Cabrejos, Thuanne Paixão, Ana Beatriz Alvarez, Diodomiro Baldomero Luque

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Research on a Density-Based Clustering Method for Eliminating Inter-Frame Feature Mismatches in Visual SLAM Under Dynamic Scenes by Zhiyong Yang, Kun Zhao, Shengze Yang, Yuhong Xiong, Changjin Zhang, Lielei Deng, Daode Zhang

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A Feasibility Study of Broadband White Light Emitting Diode (WLED) Based Full-Field Optical Coherence Microscopy (FF-OCM) Using Derivative-Based Algorithm by Tulsi Anna, Ting-Wei Chang, Chih-Ming Lai, Arthur Chiou, Wen-Chuan Kuo

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Application of machine learning algorithms to model predictors of informed contraceptive choice among reproductive age women in six high fertility rate sub Sahara Africa countries by Mequannent Sharew Melaku, Lamrot Yohannes, Berhanu Sharew, Mintesnot Hawaz Derseh, Eliyas Addisu Taye

“…Finally, we recommend that future research validate these findings using external data sources.…”
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Mapping Gridded GDP Distribution of China Based on Remote Sensing Data and Machine Learning Methods by Saimiao Liu, Wenliang Liu, Yi Zhou, Shixin Wang, Futao Wang, Zhenqing Wang

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Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan by Ahmed Emara, Sameh A. Kantoush, Mohamed Saber, Tetsuya Sumi, Vahid Nourani, Emad Mabrouk

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A global Swin-Unet Sentinel-2 surface reflectance-based cloud and cloud shadow detection algorithm for the NASA Harmonized Landsat Sentinel-2 (HLS) dataset by Haiyan Huang, David P. Roy, Hugo De Lemos, Yuean Qiu, Hankui K. Zhang

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Landslide susceptibility evaluation and determination of critical influencing factors in eastern Sichuan mountainous area, China by Lin Zhang, Zhengxi Guo, Shi Qi, Tianheng Zhao, Bingchen Wu, Peng Li

“…Geographical environment factors could indirectly affect changes in vegetation features, thereby indirectly affecting the spatial distribution of shallow landslides susceptibility. …”
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Deep learning-based time series prediction for precision field crop protection by Tao He, Meijin Li, Dong Jin

“…Traditional time series models struggle with complex agricultural data due to heterogeneity, high dimensionality, and strong spatial-temporal dependencies. These limitations hinder their ability to provide actionable insights for resource optimization and environmental protection.MethodsTo tackle these difficulties, this research puts forward a new deep-learning-based architecture for time-series prediction that is customized for precise field crop protection. …”
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Consumer-Centered Collaborative Governance of Regional Business Environment by Tingting Xiang, Hongzhi Lin

“…Investigating how the government can effectively improve the business environment and promote consumer welfare through scientific and strategic investment allocation is a topic that warrants comprehensive and in-depth research. This paper proposes a bi-level programming model based on consumer welfare, with the upper-level model focusing on optimizing the government’s investment allocation strategy to maximize consumer welfare, and the lower-level model addressing the spatial price equilibrium problem after improving the business environment. …”
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