Results 131 to 140 of about 7,675,718 (246)

Assessment of Virtual Peer Learning by Peer Feedback: A Pilot Project. [PDF]

open access: yesCureus, 2022
Uthraraj NS   +8 more
europepmc   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani   +7 more
wiley   +1 more source

Achievement Matters: External Peer Review of Accounting Learning Standards: Final Report

open access: yes, 2015
This project was led jointly by Phil Hancock and Mark Freeman, together with a project team comprising highly regarded colleagues from the accounting discipline. The project was commissioned by the Australian Business Deans Council as a follow on project
Abraham, Anne (R14556)   +6 more
core  

Investigating the Low‐Temperature Phase Stability of the Binary Ta–W System

open access: yesAdvanced Engineering Materials, EarlyView.
Atomistic simulations show that the binary Ta–W system forms ordered intermetallic phases, B2‐TaW and D03‐TaW3, as 0 K ground states. Configurational entropy, however, lowers the free energy of the disordered bcc solid solution, which becomes the stable phase above about 400 K.
Klemens Lechner   +7 more
wiley   +1 more source

Introducing the SAPS System and a Corresponding Allocation Mechanism for Synchronous Online Reciprocal Peer Support Activities [PDF]

open access: yes
While student populations in higher education are becoming more heterogeneous, recently several attempts have been made to introduce online peer support to decrease the tutor load of teachers.
Jan van Bruggen   +3 more
core  

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose   +7 more
wiley   +1 more source

Implementation of coaching and peer learning collaboratives to support home visiting practices. [PDF]

open access: yesInfant Ment Health J
McKelvey LM   +7 more
europepmc   +1 more source

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