Deep Underground Science and Engineering, EarlyView.The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li +4 more
wiley +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Epilepsia Open, EarlyView.Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Energy Science &Engineering, EarlyView.This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif +5 more
wiley +1 more source
CCC-GPU: a graphics processing unit (GPU)-accelerated nonlinear correlation coefficient for large-scale transcriptomic analyses. [PDF]
BioinformaticsZhang H +3 more
europepmc +1 more source
Environmental Control for Edible Fungi Cultivation Based on Temporal Information and Deep Learning
Food Bioengineering, EarlyView.ABSTRACT Currently, there are still prevalent issues in greenhouse environmental regulation, such as response lag, low control accuracy, and difficulty in coping with sudden environmental disturbances. To achieve high‐precision and dynamic control of the edible fungi cultivation environment, this study proposes an edible fungi environmental control ...
Xiangyan Wang +3 more
wiley +1 more source
Efficient numerical approaches with accelerated graphics processing unit (GPU) computations for Poisson problems and Cahn-Hilliard equations. [PDF]
AIMS MathOrizaga S, Fabien M, Millard M.
europepmc +1 more source
Subspace Acceleration for Efficient Nonlinear Water Wave Simulation
International Journal for Numerical Methods in Fluids, EarlyView.We introduce an exponentially weighted subspace acceleration technique to reduce GMRES iterations for solving the Poisson equation with time‐dependent coefficients in nonlinear, dispersive free‐surface flows governed by the incompressible Navier‐Stokes equations. The method significantly reduces memory requirements and computational complexity compared
Rasmus Kleist Hørlyck Sørensen +3 more
wiley +1 more source
Harnessing the Potential of LLMs in Hospital Management: Insights Into Medical Data Inquiry
The International Journal of Health Planning and Management, EarlyView.ABSTRACT Background Considering the rapid expansion of hospital operations and the increasing digitisation of medical data, there is a pressing need for efficient and intelligent methods to process and analyse large‐scale medical data. Methods We integrated the QLoRA algorithm with ChatGLM2‐6b, Llama2‐7b, and Llama2‐13b models, fine‐tuning them on a ...
Jiaxi Li +4 more
wiley +1 more source
Global optimization tailored for graphics processing units: Complete and rigorous search for large-scale nonlinear minimization. [PDF]
PNAS NexusZhang G, Shan Q, Cagan J.
europepmc +1 more source
Autonomous Velocity Encoding (VENC) Selection Improves Precision of Quantitative Flow Measurement
Journal of Magnetic Resonance Imaging, EarlyView.ABSTRACT Background The optimal velocity encoding limit (VENC) in phase contrast MRI is subject‐specific because it depends on peak flow rate and the presence of flow jets. Currently, VENC is set manually with limited prior knowledge of the peak velocity. Setting the correct VENC might improve measurement precision or shorten scan times.
Pierre Daudé +9 more
wiley +1 more source