A Synthetic Data Generation Approach With Dynamic Camera Poses for Long-Range Object Detection in AI Applications by Misbah Bibi, Anam Nawaz Khan, Muhammad Faseeh, Qazi Waqas Khan, Rashid Ahmad, do-Hyeun Kim

“…However, existing datasets often lack the complexity needed to represent real-world outdoor environments, resulting in limited performance of object detection algorithms at extended distances.Synthetic data generation offers a way to address these limitations by creating varied and realistic training scenarios. …”
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From community to science to community, enhancing remote sensing of water quality in Chesapeake Bay tributaries through participatory science by Min-Sun Lee, Maria Tzortziou, Ji-Eun Park, Tong Lin, Patrick Neale, Shelby Brown, Tara Sill, Alison Cawood

“…Our results highlight the significant benefits of engaging volunteers in estuarine water quality monitoring activities, particularly for participatory data collection, standardized data collection across coastal systems, and improvement of satellite biogeochemical retrievals in complex nearshore waters that directly impact coastal communities and economies.…”
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An advanced structural health monitoring IoT platform for offshore wind turbine blades by Zhou Xingguo, Tian Yankang, Qin Yi, Charitidis Costas A., Milickovic Tanja K., Termine Stefania

“…This research focuses on developing a comprehensive, real-time monitoring system that utilises advanced sensor networks and edge computing, empowering advanced predictive algorithms to strengthen in-time maintenance of turbine blades, improving operational efficiency and reducing maintenance cost.…”
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Reactive power optimization via deep transfer reinforcement learning for efficient adaptation to multiple scenarios by Congbo Bi, Di Liu, Lipeng Zhu, Chao Lu, Shiyang Li, Yingqi Tang

“…Supervised learning is applied in specific dynamic learning for extracting unique dynamics from offline data, which improves data efficiency and speeds up knowledge transfer. …”
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Multi-Source Heterogeneous Data-Driven Digital Delivery System for Oil and Gas Surface Engineering by Wei Zhang, Zhixiang Dai, Taiwu Xia, Gangping Chen, Yihua Zhang, Jun Zhou, Cui Liu

“…Validated through practical engineering cases, the platform enables real-time linkage of equipment parameters, documentation, and three-dimensional models, significantly improving data integration efficiency and decision-making capabilities. …”
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Spatial and Temporal Interplay Between Oceanic Circulation and Biological Production in Shaping Carbon Export Off the California Coast by M. Messié, C. L. Huffard, M. R. Stukel, H. A. Ruhl

“…These results provide insights on export spatiotemporal patterns and a path toward improving satellite‐derived carbon export in the California Current and beyond.…”
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A comprehensive review of remote sensing techniques for monitoring Ulva prolifera green tides by Xiaomeng Geng, Xiaomeng Geng, Xiaomeng Geng, Huiru Li, Huiru Li, Le Wang, Weidong Sun, Yize Li

“…Additionally, it identifies the limitations and unresolved challenges in current approaches, such as constraints on data resolution, algorithmic biases, and environmental variability. The potential for integrating multi-source remote sensing data with marine environmental parameters and deep learning techniques is discussed, emphasizing their roles in improving the accuracy and reliability of monitoring and predicting Ulva prolifera green tides. …”
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WMRCA + : a weighted majority rule-based clustering method for cancer subtype prediction using metabolic gene sets by Guojun Liu, Zhaopo Zhu, Yongqiang Xing, Hu Meng, Khyber Shinwari, Ningkun Xiao, Guoqing Liu

“…WMRCA + provides robust, interpretable, and biologically meaningful clustering results, offering a valuable tool for improving the accuracy of cancer subtype prediction. …”
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Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

“…Traditionally, interpolation methods such as Kriging have been widely used to deal with data gaps; however, their predictive accuracy in regions with sparse data still needs improvement. In recent years, the rapid development of artificial intelligence has opened up a new opportunity for data prediction. …”
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Optimization of sports injury treatment through artificial intelligence: Methods for effective prevention, diagnosis and rehabilitation by Kimi Milić Marko, Sinanović Šćepan, Jestrović Vladimir

“…The study results indicate substantial improvements in treatment efficiency, reduced recovery time, and increased diagnostic accuracy, directly facilitating a faster return to sporting activities. …”
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A Hierarchical Framework for Selecting Reference Measures for the Analytical Validation of Sensor-Based Digital Health Technologies by Jessie P Bakker, Samantha J McClenahan, Piper Fromy, Simon Turner, Barry T Peterson, Benjamin Vandendriessche, Jennifer C Goldsack

“…The digital clinical measures they generate offer enormous benefits, including providing more patient-relevant data, improving patient access, reducing costs, and driving inclusion across health care ecosystems. …”
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Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

“…Evaluating the results of image denoising algorithms in Computed Tomography (CT) scans typically involves several key metrics to assess noise reduction while preserving essential details. …”
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Extracorporeal cardiopulmonary resuscitation for refractory out‐of‐hospital cardiac arrest: Lessons learned from recent clinical trials by Stephanie DeMasi, Megan Donohue, Lisa Merck, Jarrod Mosier, for the Strategies to Innovate Emergency Care Clinical Trials Network (SIREN) investigators

“…The existing observational data combined with the latest clinical trials suggest ECPR improves mortality in patients in refractory arrest. …”
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Mapping Temperate Savanna in Northeastern China Through Integrating UAV and Satellite Imagery by Xiaoya Li, Tao Duan, Kaijie Yang, Bin Yang, Chunmei Wang, Xin Tian, Qi Lu, Feng Wang

“…The resulting map significantly improves understanding of the spatial distribution and extent of temperate savannas. …”
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Population-level predictive variation in machine learning diagnosis of symptomatic bacterial vaginosis by Diandra P. Ojo, Cameron Celeste, Dion Ming, Ruogu Fang, Ivana K. Parker

“…Future research aims to explore these factors and validate findings in larger, more diverse cohorts, with the goal of improving BV diagnosis and mitigating health disparities across ethnic groups.…”
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Advanced 5G Channel Estimation in mmWave MIMO Systems: Leveraging Compressive Sensing for Enhanced Performance by Zaid Albataineh, Mohammad Al Bataineh, Khaled Farouq Hayajneh, Raed Al Athamneh

“…Furthermore, the proposed technique achieves a substantial reduction in computational complexity and pilot overhead compared to traditional channel estimation methods, offering significant improvements in the performance of mmWave MIMO systems.…”
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AI-Driven Future Farming: Achieving Climate-Smart and Sustainable Agriculture by Karishma Kumari, Ali Mirzakhani Nafchi, Salman Mirzaee, Ahmed Abdalla

“…Using sophisticated algorithms to predict soil conditions, improving agricultural yield projections, diagnosing water stress from sensor data, and identifying plant diseases and weeds through image recognition, crop mapping, and AI-guided crop selection are some of the main applications investigated. …”
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Optimal 5G Network Sub-Slicing Orchestration in a Fully Virtualised Smart Company Using Machine Learning by Abimbola Efunogbon, Enjie Liu, Renxie Qiu, Taiwo Efunogbon

“…The framework leverages the LazyPredict module to automatically select optimal supervised learning algorithms based on real-time network conditions and historical data. …”
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Sentinel-3 Altimetry Thematic Products for Hydrology, Sea Ice and Land Ice by Jérémie Aublanc, Julien Renou, Fanny Piras, Karina Nielsen, Stine K. Rose, Sebastian B. Simonsen, Sara Fleury, Stefan Hendricks, Nicolas Taburet, Giovanni D’Apice, Anouk Chamayou, Pierre Féménias, Filomena Catapano, Marco Restano

“…The major results and outcomes are presented, showing the significant performance improvement achieved in comparison to previous processing versions.…”
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A Systematic Literature Review: Fourier Analysis as a Mathematical Tool for Robot Navigation by Prithvi Narayan, Sandeep Ameet Kumar, Avinesh Prasad, Bibhya Nand Sharma

“…The introduction of Fourier analysis or series in robot navigation algorithms greatly improves the capability to find solutions to many inherent applications and tasks of robotic systems. …”
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