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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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

“…For two of those pipelines, Common Spatial Patterns (CSP) and Short Time Fourier Transform (STFT) were successfully used as feature extraction algorithms where both these algorithms are significantly new for meditation EEG. …”
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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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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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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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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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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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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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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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Contrasting spatial variations between above and below-ground net primary productivity in global grasslands by Ying Hu, Yue Yang, Yu Wei, Xiaozhen Li, Yue Jiao, Jiapei Liao, Ruiyu Fu, Lichong Dai, Zhongmin Hu

“…However, the spatial pattern and influencing factors of NPP and its components, especially the belowground net primary productivity (BNPP) remain unclear. …”
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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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Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method by Fachri Ayudi Fitrony, Laksmita Dewi Supraba, Tessa Rantung, I Made Artha Agastya, Kusrini Kusrini

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FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging by Abhilasha Dave, Cong Wang, James Russell, Ryan Herbst, Jana Thayer

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Psychotherapist remarks’ ML classifier: insights from LLM and topic modeling application by Alexander Vanin, Vadim Bolshev, Anastasia Panfilova

“…The trained classifier demonstrates robust performance in distinguishing these thematic patterns.DiscussionThe study shows that automated topic modeling, combined with expert input, can effectively uncover how therapist language patterns emerge and persist across different therapeutic styles. …”
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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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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…The growing availability of wearable devices capable of real-time HRV data collection opens up opportunities for early detection and health status classification using machine learning. ObjectiveThis study aimed to identify HRV patterns capable of distinguishing individuals with active COVID-19 and post–COVID-19 condition and healthy controls using data collected from wearable devices and processed using machine learning models. …”
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Temporal and Spatial Dynamics of Dust Storms in Uzbekistan from Meteorological Station Records (2010–2023) by Natella Rakhmatova, Bakhriddin E. Nishonov, Lyudmila Shardakova, Albina Akhmedova, Alisher Khudoyberdiev, Valeriya Rakhmatova, Dmitry A. Belikov

“…This study highlights the importance of regional wind patterns and geomorphology in SDS formation, with prevailing wind directions from the northwest, west, and south. …”
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IDEEA: information diffusion model for integrating gene expression and EEG data in identifying Alzheimer’s disease markers by Enes Ozelbas, Tuba Sevimoglu, Tamer Kahveci

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Causal Discovery Analysis Reveals Global Sources of Predictability for Regional Flash Droughts by Sudhanshu Kumar, Di Tian

“…CENs revealed that the Indian Ocean Dipole, Pacific North Atlantic patterns, Bermuda high‐pressure system, and teleconnection patterns via Rossby wave train and jet streams strongly influence FDs in these regions. …”
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ICARus: a pipeline to extract robust gene expression signatures from transcriptome datasets by Zhaorong Li, Juan I. Fuxman Bass, Juan I. Fuxman Bass, Juan I. Fuxman Bass, Juan I. Fuxman Bass

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