Modeling and optimization of renewable hydrogen systems: A systematic methodological review and machine learning integration by Mulako Mukelabai, Edward Barbour, Richard Blanchard

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Adaptive frameworks for robust myoelectric hand gesture prediction using machine learning and deep learning by Carl Robinson

“…The research conducted herein places a focus on supplying reliable operational performance and movement dexterity via myoelectric control using machine learning (ML) and deep learning (DL) strategies. …”
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Supplementary information files for "Modeling and optimization of renewable hydrogen systems: A systematic methodological review and machine learning and integration" by Richard Blanchard, Mulako Mukelabai, Edward Barbour

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A real-time machine learning-based methodology for short-term frequency nadir prediction in low-inertia power systems by MJ Jiménez-Navarro, JM Riquelme-Dominguez, M Carranza-García, Francisco Gonzalez-Longatt

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Supplementary files for "Modeling and optimization of renewable hydrogen systems: A systematic methodological review and machine learning integration" - Load Calculation Tool by Richard Blanchard, Edward Barbour, Mulako Mukelabai

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Advancing healthcare AI: Methods to improve robustness, transparency and user-centric integration by Andrew Houston

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Machine learning force fields based on local parametrization of dispersion interactions: Application to the phase diagram of C₆₀ by Heikki Muhli, Xi Chen, Albert P Bartók, Patricia Hernández-León, Gábor Csányi, Tapio Ala-Nissila, Miguel A Caro

“…We present a comprehensive methodology to enable the addition of van der Waals (vdW) corrections to machine learning (ML) atomistic force fields. …”
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Supplementary information files for: Machine learning force fields based on local parametrization of dispersion interactions: Application to the phase diagram of C₆₀ by Heikki Muhli, Xi Chen, Albert P Bartók, Patricia Hernández-León, Gábor Csányi, Tapio Ala-Nissila, Miguel A Caro

“…Supplementary files for article: Machine learning force fields based on local parametrization of dispersion interactions: Application to the phase diagram of C60.We present a comprehensive methodology to enable the addition of van der Waals (vdW) corrections to machine learning (ML) atomistic force fields. …”
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EEG based arm movement intention recognition towards enhanced safety in symbiotic Human-Robot Collaboration by Achim Buerkle, Will Eaton, Niels Lohse, Tom Bamber, Pedro Ferreira

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Chemical, biological, radiological and nuclear event detection and classification using ontology interrogation and Social Media data by Alrefaie Mohamed, Tom Jackson, Ejovwoke Onojeharho, Elayan Suzanne

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Enhancing automated bug report analysis through advanced neural language models by Guoming Long

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A new integrated collision risk assessment methodology for autonomous vehicles by Christos Katrakazas, Mohammed Quddus, Wen-Hua Chen

“…Following the formulation and explanation of the required functions, machine learning classifiers were utilized for the real-time network-level collision prediction and the results were then incorporated into the integrated DBN model for predicting collision probabilities in real-time. …”
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Building accurate exchange-correlation functional for density functional theory through data analytics and optimization by Junfeng Zhao, Lixin Tang, Jiyin Liu, Jian Wu, Xiangman Song

“…In this study, we introduce a novel approach for XC functional modeling by fusing shared representation learning. …”
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Developing transferable real-time crash prediction models for highly imbalanced data by Cheuk Ki Man

“…Due to their simplicity in application, various statistical and machine learning models have utilised this methodology in real-time crash prediction which attained satisfactory predictability. …”
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Text-detection and -recognition from natural images by Hanaa Mahmood

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Retrosynthesis report for the 10 best-ranked routes for IM-204 by Rodolfo Teixeira, Brahim Benyahia

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Newton-X platform: new software developments for surface hopping and nuclear ensembles by Mario Barbatti, Mattia Bondanza, Rachel Crespo-Otero, Baptiste Demoulin, Pavlo O Dral, Giovanni Granucci, Fábris Kossoski, Hans Lischka, Benedetta Mennucci, Saikat Mukherjee, Marek Pederzoli, Maurizio Persico, Max Pinheiro Jr, Jirí̌ Pittner, Felix Plasser, Eduarda Sangiogo Gil, Ljiljana Stojanovic

“…Newton-X is an open-source computational platform to perform nonadiabatic molecular dynamics based on surface hopping and spectrum simulations using the nuclear ensemble approach. …”
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Application of response surface-corrected finite element model and Bayesian neural networks to predict the dynamic response of forth road bridges under strong winds by Yan Liu, Liangliang Hu, Xiaolin Meng, Yan Bao, Craig Hancock

“…This work proposes a dual-driven approach, integrating machine learning and FEM with GNSS and Earth Observation for Structural Health Monitoring (GeoSHM), to bridge the gap in the limited application of dual-driven methods primarily applied for small- and medium-sized bridges to large-span bridge structures. …”
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Artificial intelligence and art history: looking at images in an algorithmic culture by Kathryn Brown

“…Contributors explore recent developments in machine learning and computer vision and debate whether algorithmic analyses of art open new possibilities for human seeing. …”
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Data-driven analysis of decision-making in football by Chaoyi Gu

“…We contribute to the field by solving these challenges and introducing novel Machine Learning techniques, which can be used to evaluate on-pitch decisions more accurately with contextualised modelling.…”
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Probabilistic reasoning for automotive systems by Rhys Comissiong

“…This can potentially lead to the reduction of physical sensors and actuators used on internal combustion engines and other applications.With the increase in computational efficiency, Artificial Intelligence and Machine Learning techniques have gained popularity. …”
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