Interpretable machine learning model of effective mass in perovskite oxides with cross-scale features by Changjiao Li, Zhengtao Huang, Hua Hao, Zhonghui Shen, Guanghui Zhao, Ben Xu, Hanxing Liu

“…The interpretability of machine learning reveals associations between input features and predicted physical properties in models, which are essential for discovering new materials. …”
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HSM-QA: Question Answering System Based on Hierarchical Semantic Matching by Jinlu Zhang, Jing He, Yiyi Zhou, Xiaoshuai Sun, Xiao Yu

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Detection of Epilepsy Disorder Using Spectrogram Images Generated From Brain EEG Signals by Venkatesh Bhandage, Tejeswar Pokuri, Devansh Desai, Andrew Jeyabose

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Design and Optimization of a Novel Compliant Z-Positioner for the Nanoindentation Testing Device by Minh Phung Dang, Thanh Dat Le, Hieu Giang Le, Chi Thien Tran

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Experimental Study on Long Short-term Memory Networks for Identifying P-wave Primary Phase by Tianzhe WANG, Wanji ZHANG, Shanbo QI, Guoming JIANG

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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…In this context, this study proposes a methodology that combines data mining (DM) and machine learning (ML) to analyze and predict the root causes of detractors using transactional data from the big data repository of a major sports retail company. …”
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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study by Hussam J. Khasawneh, Waseem M. Al-Khatib, Zaid A. Ghazal, Ahmad M. Al-Hadi, Zaid M. Arabiyat, Osama Habahbeh

“…Our approach overcomes these limitations by employing ML algorithms to accurately predict solar generation patterns, enabling more efficient scheduling of electrical appliances. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Machine learning models were developed to classify suspicious web domains and predict their vulnerability to XSS attacks. Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Strong parameter hierarchy in the interstellar phosphorus chemical network by Marina Fernández-Ruz, Marina Fernández-Ruz, Izaskun Jiménez-Serra, Mario Castro, Mario Castro, Marta Ruiz-Bermejo, Jacobo Aguirre, Jacobo Aguirre

“…The simplified model retains its predictive accuracy, offering deeper insights into the mechanisms driving phosphorus chemistry in the interstellar medium. …”
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Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Mapping the landscape of AI and ML in vaccine innovation: A bibliometric study by Jirui Niu, Ruotian Deng, Zipu Dong, Xue Yang, Zhaohui Xing, Yin Yu, Jian Kang

“…By leveraging data-driven insights and predictive modeling, AI can streamline processes such as antigen discovery, clinical trial design, and risk assessment, thereby enabling faster responses to public health emergencies. …”
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Study of model construction of fuel production from waste plastic pyrolysis based on machine learning by CHEN Sihan, YUAN Zhilong, WANG Ye, SUN Yifei*

“…The Gradient Boosting Regression (GBR) algorithm has the best fitting performance for predicting oil yield (R^2=0.91, RMSE=7.78), while the adaptive boosting algorithm (AdaBoost) has the best fitting performance for predicting gas yield (R^2=0.83, RMSE=6.42), enabling accurate prediction of reaction conditions. …”
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PFML: Self-Supervised Learning of Time-Series Data Without Representation Collapse by Einari Vaaras, Manu Airaksinen, Okko Rasanen

“…This paper introduces a novel SSL algorithm for time-series data called Prediction of Functionals from Masked Latents (PFML). …”
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Clinical and economic analysis as an instrument for harmonizing import substitution in the preferential segment of medicinal support by E. V. Eliseeva, E. S. Maneeva, R. K. Goncharova, A. V. Kropotov

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High-Performance Thin PTFE-Ni Metamaterial Absorber for Ultra-Broadband Applications by Camilla C. Moro Carmo, Ursula C. Resende, Silvia C. Albuquerque, Mauricio D. Almeida

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Small Defects Detection of Galvanized Strip Steel via Schatten-<i>p</i> Norm-Based Low-Rank Tensor Decomposition by Shiyang Zhou, Xuguo Yan, Huaiguang Liu, Caiyun Gong

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Optimization and analysis of interior permanent magnet drive motor with unequal thickness magnetic poles for electric vehicle by Shilun MA, Yongyi WU, Changwei LI, Keqi CHEN

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Classification of Precipitation Types and Investigation of Their Physical Characteristics Using Three-Dimensional S-Band Dual-Polarization Radar Data by Choeng-Lyong Lee, Wonbae Bang, Chia-Lun Tsai, GyuWon Lee

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Application of Image Processing Technology in Aerobics Injury Diagnosis by Duo Zhang, Yan Tian

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An implementation of smoothed particle hydrodynamic methods for fluids problems by Nguyen Hoai Son, Nguyen Duy Hung

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