Results 171 to 180 of about 6,033,601 (388)
In Situ Graph Reasoning and Knowledge Expansion Using Graph‐PRefLexOR
Graph‐PRefLexOR is a novel framework that enhances language models with in situ graph reasoning, symbolic abstraction, and recursive refinement. By integrating graph‐based representations into generative tasks, the approach enables interpretable, multistep reasoning.
Markus J. Buehler
wiley +1 more source
Professional identification in the beginning of a teacher's career: a longitudinal study on identity formation and the basic psychological need for autonomy in VET teacher training. [PDF]
Weiß JK, Bottling M, Kärner T.
europepmc +1 more source
The life space interview in the school setting—Workshop, 1961: 4. Working paper: Training teachers in life space interviewing. [PDF]
William C. Morse
openalex +1 more source
This article presents the artificial synapse based on strontium titanate thin films via spin‐coating followed by forming gas annealing to introduce oxygen vacancies. Characterizations (X‐ray photoelectron spectroscopy, electron paramagnetic resonance, Ultraviolet photoelectron spectroscopy (UPS)) confirm increased oxygen vacancies and downward energy ...
Fandi Chen+16 more
wiley +1 more source
Inclusive Education in Primary and Secondary School: Perception of Teacher Training. [PDF]
Triviño-Amigo N+8 more
europepmc +1 more source
The article introduces WACEfNet, a new convolutional neural network architecture optimized for efficient aerial image analysis under resource constraints. It creatively integrates attention mechanisms and atrous convolutions into a compact widened residual network framework.
Md Meftahul Ferdaus+4 more
wiley +1 more source
Heart Rate Variability and Perceived Stress in Teacher Training: Facing the Reality Shock With Mindfulness? [PDF]
Beuchel P, Cramer C.
europepmc +1 more source
Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions
This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen+4 more
wiley +1 more source