Severity Classification of a Seismic Event based on the Magnitude-Distance Ratio Using Only One Seismological Station by Luis Hernán Ochoa Gutiérrez, Luis F Niño, Carlos A. Vargas

“…We trained a Support Vector Machine (SVM) algorithm with seismograph data recorded by INGEOMINAS's National Seismological Network at a three-component station located near Bogota, Colombia. …”
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Explainability of a Deep Learning-Based Classification Model for Antineutrophil Cytoplasmic Autoantibody–Associated Glomerulonephritis by Maria A.C. Wester Trejo, Maryam Sadeghi, Shivam Singh, Naghmeh Mahmoodian, Samir Sharifli, Zdenka Hruskova, Vladimír Tesař, Xavier Puéchal, Jan Anthonie Bruijn, Georg Göbel, Ingeborg M. Bajema, Andreas Kronbichler

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TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors by Zhonghuang Wang, Zhonghuang Wang, Zhe Zhang, Dongli Zhao, Dongli Zhao, Zhenglin Du, Bixia Tang, Enhui Jin, Hailong Kang, Wenming Zhao, Yuanguang Meng

“…TCR demonstrated more distinct spatial distribution patterns between benign and malignant states, suggesting its potential as a more sensitive biomarker for ovarian tumor detection. …”
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Leveraging machine learning for analyzing the nexus between land use and land cover change, land surface temperature and biophysical indices in an eco-sensitive region of Brahmani-... by Bhaskar Mandal

“…This present study aims to evaluate land use and land cover changes using five machine-learning algorithms in Google Earth Engine. …”
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A novel method for quantifying the contribution of regional transport to PM_2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory... by K. Hu, H. Liao, D. Liu, J. Jin, L. Chen, S. Li, Y. Wu, C. Wu, S. Zhao, X. Jiang, P. Tian, P. Tian, K. Bi, K. Bi, Y. Wang, Y. Wang, Y. Wang, D. Zhao, D. Zhao

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ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering by Maryam Shahabikargar, Amin Beheshti, Wathiq Mansoor, Xuyun Zhang, Eu Jin Foo, Alireza Jolfaei, Ambreen Hanif, Nasrin Shabani

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Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm by Dongjie Guan, Yitong Shi, Lilei Zhou, Xusen Zhu, Demei Zhao, Guochuan Peng, Xiujuan He

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Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network by Chinnakrit Banyong, Natthaporn Hantanong, Supanida Nanthawong, Chamroeun Se, Panuwat Wisutwattanasak, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao

“…These findings underscore the effectiveness of machine learning approaches in capturing complex behavioral patterns, providing empirical evidence to guide high-speed rail policy development in low- and middle-income countries. …”
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Integrating single cell analysis and machine learning methods reveals stem cell-related gene S100A10 as an important target for prediction of liver cancer diagnosis and immunothera... by Shenjun Huang, Tingting Tu

“…We analyzed various datasets, applying negative matrix factorization alongside machine learning algorithms to reveal gene expression patterns and construct diagnostic models. …”
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Novel machine learning-driven comparative analysis of CSP, STFT, and CSP-STFT fusion for EEG data classification across multiple meditation and non-meditation sessions in BCI pipel... by Nalinda D. Liyanagedera, Corinne A. Bareham, Heather Kempton, Hans W. Guesgen

“…This novel study focuses on using multiple sessions of EEG data from a single individual to train a machine learning pipeline, and then using a new session data from the same individual for the classification. …”
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Three Decades of Land Cover Dynamics in a Boreal Coastal Basin: A Multisensor Spectral Index and Machine Learning Approach Using Landsat Data and GB-SAR Data by Jinsong Zhang, Bochi Zou, Yifei Yuan, Asad Khan, Muhammad Bilawal Junaid, Qaiser Abbas, Rana Muhammad Zulqarnain, Nazih Y. Rebouh, Olga D. Kucher, Hassan Alzahrani

“…Using a 30-year Landsat satellite data archive (1990–2020) from Landsat 4, 5, 7, 8, and 9 sensors, we analyzed long-term changes in land cover patterns, focusing on vegetation health, surface water extent, and urban expansion. …”
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Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

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Battery Current Estimation and Prediction During Charging with Ant Colony Optimization Algorithm by Selamat Muslimin, Ekawati Prihatini, Nyayu Latifah Husni, Tresna Dewi, Mukhidin Wartam Bin Umar, Auvi Crisanta Ana Bela, Sri Utami Handayani, Wahyu Caesarendra

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Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges by Jielu Yan, Zhengli Chen, Jianxiu Cai, Weizhi Xian, Xuekai Wei, Yi Qin, Yifan Li

“…Recent advances in artificial intelligence—especially machine learning (ML), deep learning (DL), and pattern recognition—offer game-changing opportunities to accelerate AMP design and validation. …”
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Assessing the Impact of Climate Change on Winter Wheat Production in the North China Plain from 1980 to 2020 by Jinhui Zheng, Shuai Zhang

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LED-Based Collimating Line-Light Combining Freeform and Fresnel Optics by AnneMarie McCarthy, Javier Romero-Vivas, Ciara O'Hara, Natalia Rebrova, Liam Lewis, Stephen P. Hegarty

“…Illumination for line-scan machine vision systems is required to produce a highly asymmetric elliptical beam pattern, to maximize system speed and accuracy. …”
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Robust Classification of UWB NLOS/LOS Using Combined FCE and XGBoost Algorithms by Shoude Wang, Nur Syazreen Ahmad

“…Compared to traditional machine learning and neural networks, it offers lower system requirements. …”
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Optimising Mechanical Performance of Additive Manufactured Composites for Biomedical Applications by Abdul Qadir, Amadi Gabriel Udu, Norman Osa-uwagboe

“…While previous studies have explored the role of process parameters in optimising AM components, the impact of infill geometry on anisotropy and mechanical performance remains underexplored, particularly in the context of machine learning (ML). This study develops an ML-driven framework to predict the tensile and flexural properties of AM SFRP composites with different infill patterns, including triangular, hexagonal, and rectangular. …”
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Socioeconomic status (SES) and cognitive outcomes are predicted by resting-state EEG in school-aged children by Julie M. Schneider, Jeahong Kim, Sonali Poudel, Yune S. Lee, Mandy J. Maguire

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Emotion Recognition in Gaming Dataset to Reduce Artifacts in the Self-Assessed Labeling Using Semi-Supervised Clustering by Oscar Almanza-Conejo, Juan Gabriel Avina-Cervantes, Arturo Garcia-Perez, Mario Alberto Ibarra-Manzano

“…Besides, a 1-D Local Binary Pattern (LBP) method transforms the EEG temporal behavior to extract time-frequency features. …”
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