Machine learning-based retrieval of total column water vapor over land using GMI-sensed passive microwave measurements by Jiafei Xu, Zhizhao Liu

“…It is challenging to retrieve TCWV over land from satellite MW measurements because of varying land surface characteristics. In this paper, a novel Light Gradient Boosting Machine-based retrieval algorithm is proposed to derive TCWV over land from GMI-sensed MW brightness temperature (BT) observations. …”
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Flow dynamics in a vertical pipe with internal fins exposed to sunlight – A machine learning based evaluation of thermal signature by Assmaa Abd-Elmonem, Zill E Shams, Mariam Imtiaz, Kashif Ali, Sohail Ahmad, Wasim Jamshed, Fayza Abdel Aziz ElSeabee, Neissrien Alhubieshi, Syed M. Hussain, Hijaz Ahmad

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Fortified-Edge 2.0: Advanced Machine-Learning-Driven Framework for Secure PUF-Based Authentication in Collaborative Edge Computing by Seema G. Aarella, Venkata P. Yanambaka, Saraju P. Mohanty, Elias Kougianos

“…Unlike conventional methods that transmit full binary Challenge–Response Pairs (CRPs) and risk exposing sensitive data, Fortified-Edge 2.0 employs a machine-learning-driven feature-abstraction technique to extract and utilize only essential characteristics of CRPs, obfuscating the raw binary sequences. …”
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A Novel Damage Inspection Method Using Fluorescence Imaging Combined with Machine Learning Algorithms Applied to Green Bell Pepper by Danial Fatchurrahman, Noelia Castillejo, Maulidia Hilaili, Lucia Russo, Ayoub Fathi-Najafabadi, Anisur Rahman

“…Fluorescence imaging has emerged as a powerful tool for detecting surface damage in fruits, yet its application to vegetables such as green bell peppers remains underexplored. …”
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Exergy and energy-based sustainability evaluation of diesel-biodiesel-ethanol blends with emission forecasting using advanced machine learning models by Harish Venu, V. Dhana Raju, Jayashri N. Nair, Sameer Algburi, Ali E. Anqi, Ali A. Rajhi, Mohammed Kareemullah

“…To optimize fuel parameters, the Desirability Function Approach (DFA) integrated with Response Surface Methodology (RSM) was employed. Additionally, advanced machine learning (ML) techniques were utilized to predict these performance characteristics. …”
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Concrete Spalling Severity Classification Using Image Texture Analysis and a Novel Jellyfish Search Optimized Machine Learning Approach by Nhat-Duc Hoang, Thanh-Canh Huynh, Van-Duc Tran

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Automatic delineation of cervical cancer target volumes in small samples based on multi-decoder and semi-supervised learning and clinical application by Haibo Peng, Tao Liu, Pengcheng Li, Fang Yang, Xing Luo, Xiaoqing Sun, Dong Gao, Fengyu Lin, Lecheng Jia, Ningyue Xu, Huigang Tan, Xi Wang, Tao Ren

“…According to the data characteristics for small samples, the MDSSL network structure based on 3D U-Net was established to train the model by combining clinical anatomical information, which was compared with other segmentation methods, including supervised learning (SL) and transfer learning (TL). …”
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Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…All input datasets (as input factors for machine learning algorithms) were co-registered to match the resolution of the InSAR-derived maps (100 meters).Machine learning algorithms: Three machine learning algorithms including decision tree (DT), random forest (RF) and extreme gradient boosting (XGBoost) were tested. …”
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Mapping burnt areas using very high-resolution imagery and deep learning algorithms - a case study in Bandipur, India. by Sai Balakavi, Vineet Vadrevu, Kristofer Lasko

“…Accurate BA data helps estimate carbon emissions, biodiversity loss, and land surface properties post-fire changes. In this study, we designed and evaluated two deep learning-based architectures, a Custom UNET and a novel UNET-Gated Recurrent Unit (GRU), for burnt area classification using PlanetScope data over Bandipur, India. …”
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The Machine Learning-Based Mapping of Urban Pluvial Flood Susceptibility in Seoul Integrating Flood Conditioning Factors and Drainage-Related Data by Julieber T. Bersabe, Byong-Woon Jun

“…In the last two decades, South Korea has seen an increase in extreme rainfall coinciding with the proliferation of impermeable surfaces due to urban development. When underground drainage systems are overwhelmed, pluvial flooding can occur. …”
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Gesture Recognition System Based on Time-Frequency Point Density of sEMG by Qiang Wang, Yao Chen, Chunhua Sheng, Shuaidi Song

“…It is usually realized by extracting the characteristics of different finger movements and then using machine learning or deep learning algorithms to classify and recognize them. …”
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Development and Evaluation of Machine Learning Models for Air-to-Land Temperature Conversion Using the Newly Established Kunlun Mountain Gradient Observation System by Yongkang Li, Qing He, Yongqiang Liu, Amina Maituerdi, Yang Yan, Jiao Tan

“…We constructed a conceptual model to explore the relationship between 1.5 m TA and LST and instantiated it using three machine learning algorithms: Support Vector Machine (SVR), Convolutional Neural Network (CNN), and CatBoost. …”
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A cluster-based local modeling paradigm for high spatiotemporal resolution VPD prediction using multi-source data and machine learning by Mi Wang, Zhuowei Hu, Xiangping Liu, Wenxing Hou

“…This study introduces a Cluster-Based Local Modeling (CBLM) paradigm, integrating meteorological data, surface characteristics, and in situ observations to achieve high-precision VPD prediction using machine learning. …”
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Experimental investigation and laser control in Ti10Mo6Cu powder bed fusion: optimizing process parameters with machine learning by Ouf A. Shams, Hanan B. Matar Al-Baity, Luttfi A. Al-Haddad

“…This study presents a hybrid experimental and machine learning (ML) approach to enhance laser control in the LPBF process for Ti10Mo6Cu alloys. …”
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Upper limb human-exoskeleton system motion state classification based on semg: application of CNN-BiLSTM-attention model by Dongwei Zhao, Xiangming Ye, Song Wang, Chenfeng Zhang, Shouqian Sun, Xuequn Zhang, Ruidong Cheng

“…Abstract This study aims to classify five typical motion states of the human upper limb based on surface electromyography signals, thereby supporting the real-time control system of an assistive upper limb exoskeleton. …”
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Forest stand and soil types determine soil organic carbon storage in the Middle Atlas region of Morocco using machine learning models by Mohamed El Mderssa, Meysara Elmalki, Joann K. Whalen, Hicham Ikraoun, Fatima Zahra Aliyat, Youssef Dallahi, Younes Abbas, Laila Nassiri, Jamal Ibijbijen

“…Forest soils often contain more carbon (C) than living trees, with significant variation in soil organic carbon (SOC) stocks due to stand type and soil characteristics. This study evaluates SOC stocks in the Moroccan Middle Atlas forests using field measurements and machine learning models. …”
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Deep Learning-Assisted Microscopic Polarization Inspection of Micro-Nano Damage Precursors: Automatic, Non-Destructive Metrology for Additive Manufacturing Devices by Dingkang Li, Xing Peng, Zhenfeng Ye, Hongbing Cao, Bo Wang, Xinjie Zhao, Feng Shi

“…However, when addressing industrial-grade precision manufacturing requirements, key challenges such as the multi-scale characteristics of surface damage precursors, interference from background noise, and the scarcity of high-quality training samples severely constrain the intelligent transformation of AM quality monitoring systems. …”
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Efficacy and prognostic factors of anti-VEGF treatment for neovascular age-related macular degeneration: An OCTA imaging-based deep learning analysis by Shengnan Liu, Yuanyuan Liu, Xiaohan Wu, Haochen Wang, Ziqi Jin, Peiru Wang, Jinyu Feng, Song Chen, Wei Zhou

“…It allowed for making personalized treatment strategy to tailor interventions based on individual risk profiles and vascular characteristics which can enhance patient outcomes.…”
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Artificial Intelligent‐Enhanced Metabolite Profiling for Intraoperative IDH1 Genotyping in Glioma Using an Orthogonally Responsive SERS Probe by Hang Yin, Xin Zhang, Zheng Zhao, Chong Cao, Minhua Xu, Suhongrui Zhou, Tian Xuan, Ziyi Jin, Limei Han, Yang Fan, Cong Wang, Xiao Zhu, Ying Mao, Jinhua Yu, Cong Li

“…Additionally, a deep learning algorithm is implemented, leveraging 2D Raman spectra transformation and multi‐task learning to enhance measurement speed and accuracy. …”
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Statistical and machine learning analysis of diesel engines fueled with Moringa oleifera biodiesel doped with 1-hexanol and Zr2O3 nanoparticles by K. Sunil Kumar, Abdul Razak, M. K. Ramis, Shaik Mohammad Irshad, Saiful Islam, Anteneh Wogasso Wodajo

“…A comprehensive methodology involving experimental testing and statistical modelling using Gradient Boosting (GBoost), Extreme Learning Machine (ELM), and Response Surface Methodology (RSM) was employed. …”
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