Results 181 to 190 of about 64,270 (302)
Virtual Learning Environments In Spanish Traditional Universities
Leire Urcola, Amaia Altuzarra Artola
openalex +2 more sources
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
Application of Artificial Intelligence in Education of Prosthodontics and Implant Dentistry: A Review. [PDF]
Gan Y, Guo J, Zhai J, Huang J.
europepmc +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Toward Smart VR Education in Media Production: Integrating AI into Human-Centered and Interactive Learning Systems. [PDF]
Su Z, Tan TG, Chen L, Su H, Alfayad S.
europepmc +1 more source
Characterization of Self-Regulation of Learning as an Executive Function in Students Within Virtual Learning Environments [PDF]
Dannia Narey Vega Galvan +5 more
openalex +1 more source
Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira +13 more
wiley +1 more source
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun +8 more
wiley +1 more source

