Global Aerosol Climatology from ICESat-2 Lidar Observations by Shi Kuang, Matthew McGill, Joseph Gomes, Patrick Selmer, Grant Finneman, Jackson Begolka

“…This study presents a global aerosol climatology derived from six years (October 2018–October 2024) of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observations, using a U-Net Convolutional Neural Network (CNN) machine learning algorithm for Cloud–Aerosol Discrimination (CAD). …”
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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…To facilitate this, an automated artificial intelligence material recommendation mechanism was developed, underpinned by several machine learning models. By observing online user learning behavior patterns, learning data and indicators were formulated, enabling the analysis of various online learning behaviors (e.g., watching videos and answering practice questions) and the generation of learning processes that can be viewed by learners. …”
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Automated inflammatory bowel disease detection using wearable bowel sound event spotting by Annalisa Baronetto, Annalisa Baronetto, Sarah Fischer, Sarah Fischer, Markus F. Neurath, Markus F. Neurath, Oliver Amft, Oliver Amft

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Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

“…Action units (AUs) for each phase instance were measured using AFFDEX software. AU patterns associated with each phase were then identified through the application of six supervised machine learning algorithms. …”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…The core of this method is an improved algorithm based on the TD3, which is enhanced by the incorporation of the CQL algorithm to improve the stability of the collaborative control strategy. …”
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ML-Based Materials Evaluation in 3D Printing by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Jakub Kopowski

“…Machine learning (ML) is transforming the evaluation of 3D printing materials, enabling more efficient and accurate assessment of material properties, including their sustainable life cycle. …”
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Trustworthiness of Deep Learning Under Adversarial Attacks in Power Systems by Dowens Nicolas, Kevin Orozco, Steve Mathew, Yi Wang, Wafa Elmannai, George C. Giakos

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Anomaly detection in cropland monitoring using multiple view vision transformer by Xuesong Liu, Yansong Liu, He Sui, Chuan Qin, Yuanxi Che, Zhaobo Guo

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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

“…Our methodology, along with an updated ensemble method, bridges the gap between Explainable AI and leverages a variety of machine learning algorithms to improve predictive accuracy. …”
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AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis by Bhekisipho Twala

“…The integration of multiple data modalities and advanced machine learning algorithms enables earlier detection, more accurate monitoring, and optimized therapeutic interventions. …”
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A Novel Electromagnetic Induction-Based Approach to Identify the State of Shallow Groundwater in the Oasis Group of the Tarim Basin in Xinjiang During 2000–2022 by Fei Wang, Yang Wei, Rongrong Li, Hongjiang Hu, Xiaojing Li

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An optimized ensemble model with advanced feature selection for network intrusion detection by Afaq Ahmed, Muhammad Asim, Irshad Ullah, Zainulabidin, Abdelhamied A. Ateya

“…However, these methods often fall short in detecting sophisticated and evolving threats, particularly those involving subtle variations or mutations of known attack patterns. To address this challenge, our study presents the “Optimized Random Forest (Opt-Forest),” an innovative ensemble model that combines decision forest approaches with genetic algorithms (GAs) for enhanced intrusion detection. …”
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Identification and validation of hub genes related to neutrophil extracellular traps-mediated cell damage and immune recruitment during abdominal aortic aneurysm by Chuanlong Lu, Heng Wang, Maolin Qiao, Runze Chang, Jinshan Chen, Lizheng Li, Keyi Fan, Sheng Yan, Ruijing Zhang, Honglin Dong

“…Subsequently, utilizing bioinformatics and machine learning algorithms, candidate crucial genes were identified within NETs-related genes and transcriptome datasets (GSE179828, GSE145200, GSE161464, GSE57691, GSE232911 and GSE166676). …”
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Bio-Magneto Sensing and Unsupervised Deep Multiresolution Analysis for Labor Predictions in Term and Preterm Pregnancies by Ejay Nsugbe, Oluwarotimi Williams Samuel, Jose Javier Reyes-Lagos, Dawn Adams, Olusayo Obajemu

“…DWS is combined with select pattern-recognition-based prediction machines in order to assemble a clinical decision pipeline for the prediction of the states of various pregnancies, with a greater degree of machine intelligence. …”
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Improved Splitting-Integrating Methods for Image Geometric Transformations: Error Analysis and Applications by Hung-Tsai Huang, Zi-Cai Li, Yimin Wei, Ching Yee Suen

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Landslide and Collapse Susceptibility Analysis in Wenchuan Earthquake-damaged Area Based on Ensemble Learning Methods by DING Jiawei, WANG Xiekang

“…Recent advancements in data science and machine learning provide promising solutions. Two state-of-the-art ensemble learning algorithms, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM), are introduced to formulate dependable models for appraising susceptibility to landslides and collapses within the confines of Wenchuan County.MethodsA comprehensive evaluation of factors related to topography, geology, meteorology, and hydrology was conducted to select ten evaluative factors: Elevation, slope, aspect, terrain relief, distance to rivers, distance to faults, normalized difference vegetation index (NDVI), land cover type, average annual precipitation, and lithology. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Furthermore, the Ordered Weighted Averaging (OWA) algorithm and the Partical Swarm Optimization-Support Vector Machine (PSO-SVM) model were combined to simulate future GDV scenarios for 2030–2050 under three development preferences: environment oriented, status quo, and economically oriented. …”
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Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes by Shoupeng Ding, Chunxiao Huang, Jinghua Gao, Chun Bi, Yuyang Zhou, Zihan Cai

“…We identified T-cell-associated metabolic differentially expressed genes (TCM–DEGs) through integrated differential expression analysis and machine learning algorithms (XGBoost, SVM–RFE, and Boruta). …”
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MEMS and IoT in HAR: Effective Monitoring for the Health of Older People by Luigi Bibbò, Giovanni Angiulli, Filippo Laganà, Danilo Pratticò, Francesco Cotroneo, Fabio La Foresta, Mario Versaci

“…The analysis methods employed include machine learning algorithms to identify movement patterns, statistical analysis to assess the frequency and quality of movements, and data visualization to track changes over time. …”
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Intelligent Diagnosis and Predictive Rehabilitation Assessment of Chronic Ankle Instability Using Shoe-Integrated Sensor System by Zhonghe Guo, Yanzhang Li, Yuchen Wang, Haoxuan Liu, Rui Guo, Jingzhong Ma, Xiaoming Wu, Dong Jiang, Tianling Ren

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