Results 151 to 160 of about 333,028 (258)

Blended learning Component in nursing education: A systematic review. [PDF]

J Educ Health Promot
Toghyani A, Rahmani J, Khorasgani AT, Kalhor F, Emamjomeh SM.   +4 more
europepmc   +1 more source

Enhancing Sensitivity across Scales with Highly Sensitive Hall Effect‐Based Auxetic Tactile Sensors

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Herein, a tactile sensor based on hall‐effect sensors with an auxetic structure, called Hall effect‐based auxetic tactile sensor (HEATS), is proposed. The change in magnetism resulting from the deformation of the auxetic structure is utilized for sensing.
Youngheon Yun, Dongchan Lee, Soyeon Lee, Salvador Pané, Josep Puigmartí‐Luis, Sungwoo Chun, Bumjin Jang   +6 more
wiley   +1 more source

Interdisciplinary interactive blended learning concept in times of a pandemic - pain medicine "totally digital". [PDF]

GMS J Med Educ
Schramm L, Friedrich P, Schüttler J, Lütcke B.   +3 more
europepmc   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

THE E-LEARNING BENEFITS IN THE ROMANIAN BUSINESS ENVIRONMENT [PDF]

E-learning is learning based on information technologies, and particularly based on the Interne educational system has a lot of advantages, such as flexibility, availability, time and resources savings and it respects the individual learning rhythm of ...
Popeanga Vasile Nicolae, Vatuiu Teodora
core  

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Innovating transfusion training: a BOPPPS-based blended learning model to enhance nursing interns' specialized competency. [PDF]

Front Med (Lausanne)
Xiao N, Liu C, Mao M, Huang J, Huang Y, Wu H, Wang W.   +6 more
europepmc   +1 more source

GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation

Advanced Intelligent Systems, EarlyView.
This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li, Xiaomei Wang, Xiaoqi Song, Chenchen Fan, Bohao Zhu, Jianan Peng, Qixin Liang, James Lam, Kam‐Yim Sze, Ka‐Wai Kwok   +9 more
wiley   +1 more source

Improving medical students' learning absorption in a knowledge graph based blended learning course. [PDF]

BMC Med Educ
Li B, Hu W, Duan A, Li Q, Li L, Li C, Weng C, Peng Z, Chen W, Li Y.   +9 more
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source