Recent advances in machine learning for defects detection and prediction in laser cladding process by X.C. Ji, R.S. Chen, C.X. Lu, J. Zhou, M.Q. Zhang, T. Zhang, H.L. Yu, Y.L. Yin, P.J. Shi, W. Zhang

“…Moreover, these algorithms offer avenues for feedback regulation of the cladding process, optimizing parameters, and mitigating cladding defects, thereby establishing this as a research frontier. …”
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An AI-Based Framework for Characterizing the Atmospheric Fate of Air Pollutants Within Diverse Environmental Settings by Nataša Radić, Mirjana Perišić, Gordana Jovanović, Timea Bezdan, Svetlana Stanišić, Nenad Stanić, Andreja Stojić

“…This study introduces a novel artificial intelligence (AI) modeling framework that combines machine learning algorithms optimized through metaheuristics with explainable AI to capture complex interactions among pollutant concentrations, meteorological data, and socio-economic indicators. …”
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Multi-Attitude Hybrid Network for Remote Sensing Hyperspectral Images Super-Resolution by Chi Chen, Yunhan Sun, Xueyan Hu, Ning Zhang, Hao Feng, Zheng Li, Yongcheng Wang

“…Extensive experiments demonstrate that our method achieves optimal reconstruction results compared to other state-of-the-art algorithms while effectively reducing the computational complexity.…”
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Spatiotemporal Trends and Zoning Geospatial Assessment in China’s Offshore Mariculture (2018–2022) by Zewen Mo, Yulin Chen, Xuan Zhang, Zhipan Wang, Qingling Zhang

“…This study utilizes high-resolution remote sensing data (2017–2023) and advanced ConvNeXt V2 algorithms to quantitatively analyze the spatiotemporal dynamics of offshore mariculture and explore its spatial distribution in relation to marine functional zoning policies. …”
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Monitoring multiyear cropping patterns in the arid regions of northwestern China from 2005 to 2022 using Landsat time-series data by Yongquan Lu, Guilin Liu, Xiuyuan Zhang, Jingwen Wang, Weijia Chen, Yuecheng Li, Desheng Jiang

“…Understanding cropping patterns can help optimize crop yield while preserving ecosystems and enhancing ecological benefits. …”
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Do We Need to Add the Type of Treatment Planning System, Dose Calculation Grid Size, and CT Density Curve to Predictive Models? by Reza Reiazi, Surendra Prajapati, Leonardo Che Fru, Dongyeon Lee, Mohammad Salehpour

“…<b>Results:</b> Results showed that dose grid size differences had a more significant influence within RayStation than Pinnacle, while CT curve variations introduced potential domain discrepancies. …”
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GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…Key algorithms are systematically integrated to optimize outcomes in urban planning, disaster management, and precision agriculture. …”
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Potential of Multi-Source Multispectral vs. Hyperspectral Remote Sensing for Winter Wheat Nitrogen Monitoring by Xiaokai Chen, Yuxin Miao, Krzysztof Kusnierek, Fenling Li, Chao Wang, Botai Shi, Fei Wu, Qingrui Chang, Kang Yu

“…Results showed that, while hyperspectral data yielded slightly higher accuracy, optimized multispectral indices, particularly from PS and S2, achieved comparable performance. …”
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Bioinformatic Methodologies in Assessing Gut Microbiota by James Douglas Fox, Austin Sims, Morgan Ross, Jeffery Bettag, Alexandra Wilder, Dylan Natrop, Alison Borsotti, Sree Kolli, Shaurya Mehta, Hema Verma, Kento Kurashima, Chandrashekhara Manithody, Arun Verma, Ajay Jain

“…Bioinformatics tools and algorithms process these data to identify microbial taxa and quantify and elucidate their roles within the microbiome. …”
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Review of Maglev Train Dynamics Research by WEN Yanfeng, ZHANG Weifeng, CAI Wenfeng, XU Hao

“…[Objective] To ensure the operational stability and safety of maglev trains, current research achievements in China and abroad on maglev train dynamics performance are summarized, while prospecting future research directions. [Method] Based on UM (universal mechanism) dynamics simulation software, research findings on various aspects, including vehicle suspension parameters, suspension frame structures, multi-unit train dynamics, active suspension control algorithms, passive suspension fitting models, vehicle-track dynamics, train dynamics under crosswind loads, and bridge dynamic responses are summarized, and future research directions are prospected. …”
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Improving resectable gastric cancer prognosis prediction: A machine learning analysis combining clinical features and body composition radiomics by Gianni S.S. Liveraro, Maria E.S. Takahashi, Fabiana Lascala, Luiz R. Lopes, Nelson A. Andreollo, Maria C.S. Mendes, Jun Takahashi, José B.C. Carvalheira

“…Body composition radiomics were integrated with clinicopathological factors using machine learning (ML) algorithms trained for patient outcome prediction. We compared results using Random Forest, Logistic Regression and Boosted Decision Tree algorithms. …”
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Automated Quality Control of Cleaning Processes in Automotive Components Using Blob Analysis by Simone Mari, Giovanni Bucci, Fabrizio Ciancetta, Edoardo Fiorucci, Andrea Fioravanti

“…The LoG and DoG methods were more prone to spurious detections, while DoH demonstrated intermediate performance but struggled with reflective surfaces. …”
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Remote monitoring of Tai Chi balance training interventions in older adults using wearable sensors and machine learning by Giulia Corniani, Stefano Sapienza, Gloria Vergara-Diaz, Andrea Valerio, Ashkan Vaziri, Paolo Bonato, Peter M. Wayne

“…Data were collected from 32 participants with inertial measurement units (IMUs) while performing six Tai Chi movements evaluated and scored for adherence and proficiency by experts. …”
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Mixed Reality Human&#x2013;Robot Interface With Adaptive Communications Congestion Control for the Teleoperation of Mobile Redundant Manipulators in Hazardous Environments by Krzysztof Adam Szczurek, Raul Marin Prades, Eloise Matheson, Jose Rodriguez-Nogueira, Mario Di Castro

“…The teleoperator was provided with immersive interactions while preserving precise positioning of the robot. …”
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Enhanced Collaborative Edge Intelligence for Explainable and Transferable Image Recognition in 6G-Aided IIoT by Chen Chen, Ze Sun, Jiale Zhang, Junwei Dong, Peng Zhang, Jie Guo

“…IRCE leverages edge intelligence to optimize real-time performance while reducing computational costs and enhancing scalability. …”
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A novel hybrid deep learning approach for super-resolution and objects detection in remote sensing by Muhammad Asif, Mohammad Abrar, Faizan Ullah, Abdu Salam, Farhan Amin, Isabel de la Torre, Mónica Gracia Villar, Helena Garay, Gyu Sang Choi

“…Advanced StyleGAN enhances image resolution, facilitating the detection of small and occluded objects, while Swin Transformer employs hierarchical attention mechanisms for effective feature extraction. …”
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Advanced Hydroponic Nutrient Management Systems for Vertical Farming Efficiency with IoT and Model Predictive Control to Enhance Sustainable Crop Growth by Almusawi Muntather, Hussein Abbas Hameed Abdul, Raju V. Siva Prasada

“…In the quest to advance vertical farming efficiency, optimizing hydroponic nutrient management systems is essential for achieving high productivity and sustainability. …”
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Precision Weed Management for Straw-Mulched Maize Field: Advanced Weed Detection and Targeted Spraying Based on Enhanced YOLO v5s by Xiuhong Wang, Qingjie Wang, Yichen Qiao, Xinyue Zhang, Caiyun Lu, Chao Wang

“…This approach also promotes the application of deep learning algorithms in precision weed management within directional spraying systems.…”
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Niche Overlap Between Two Sympatric Steppe Birds in Inner Mongolia: Habitat Selection and Insights for Conservation by Zheng Han, Xi Yang, Lishi Zhang, Frédéric Jiguet, Piotr Tryjanowski, Haitao Wang

“…Jankowski's Bunting favors areas with higher vegetation cover and height, while Meadow Bunting prefers sites with greater edge density. …”
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Review and prospect of floating car data research in transportation by Chi Zhang, Yuming Zhou, Min Zhang, Bo Wang, Yuhan Nie

“…The three major research clusters include traffic flow state, traffic safety, and route planning. The optimal investment proportion for floating cars is determined to be 3%–8%, and the sampling frequency significantly affects the accuracy of vehicle speed and heading angle information, while having a weaker impact on positional parameters. …”
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