Results 201 to 210 of about 145,710 (264)

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

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, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Predicting the mechanical behavior of municipal solid waste layers in the Barmshour Landfill stability analysis. [PDF]

Sci Rep
Mokhtari MM, Falamaki A, Vafaeian M.
europepmc   +1 more source

Neural Network–Assisted Metasurface Retroreflector With Wide‐Angle Adaptivity

Electron, EarlyView.
This work proposes a wide‐angle, multi‐polarization, self‐sensing, and self‐adaptive intelligent metasurface retroreflector, with a planar profile and ultrathin thickness. By integrating a pre‐trained artificial neural network (ANN), the metasurface retroreflector can recognize the incident angle and promptly adapt to changes in the incoming wave.
Jing Ning, Xunfan Wang, Kun Duan, Weixu Yang, Junming Zhao, Tian Jiang, Ke Chen, Yijun Feng   +7 more
wiley   +1 more source

Enhanced log ratio calibration methods for stratified variance estimation in survey sampling. [PDF]

Sci Rep
Zaka A, Alghamdi FM, Alsheikh SMA, Jabeen R, Minhas KS, Bano S, Afify AZ.   +6 more
europepmc   +1 more source

An algorithm for seizure detection in rodents

Epilepsia Open, EarlyView.
Abstract Objective Epilepsy animal research often relies on long‐term intracranial electroencephalographic (iEEG) recordings. Here, we describe an artificial neural network (ANN) algorithm for automatic detection of seizures. Methods The algorithm was trained on iEEG recordings of three mouse models of chronic epilepsy: (1) the pilocarpine model of ...
Lyna Kamintsky, Gerben van Hameren, Itai Weissberg, Pooyan Moradi, Ofer Prager, Alaa Abu Ahmad, Lior Schori, Albert Becker, Yaniv Zigel, Alon Friedman   +9 more
wiley   +1 more source

Precipitation modeling in Northeastern Bangladesh-India transboundary flood regions using bi-metaheuristic-optimized NMF-neural network. [PDF]

Sci Rep
Shuvo SP, Shibazee SP, Das C, Oishi AB.
europepmc   +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, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

AI-Driven prediction of body weight in chicken genotypes with different growth rates. [PDF]

Trop Anim Health Prod
Musa AA, Idrus Z, Chung ELT, Samat N, Abdulkadir RA, Abayomi RE, Setiaji A, Mamat-Hamidi K.   +7 more
europepmc   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Modelling C-arm fluoroscopy and operating table kinematics via machine learning. [PDF]

Front Robot AI
Jaheen F, Gutta V, Fallavollita P.
europepmc   +1 more source