Results 71 to 80 of about 636,159 (270)

A Variational Beam Model for Failure of Cellular and Truss‐Based Architected Materials

Advanced Engineering Materials, EarlyView., 2023
Herein, a versatile and efficient beam modeling framework is developed to predict the nonlinear response and failure of cellular, truss‐based, and woven architected materials. It enables the exploration of their design space and the optimization of their mechanical behavior in the nonlinear regime. A variational formulation of a beam model is presented
Konstantinos Karapiperis, Kaoutar Radi, Zifan Wang, Dennis M. Kochmann   +3 more
wiley   +1 more source

Examining Adaptive E-Learning Approaches to Enhance Learning and Individual Experiences

Acta Informatica Pragensia
The concept of individualization has emerged as an essential advance in education, representing a paradigm shift adopted by educational systems worldwide. This paradigm evolution aims to optimize student performance by harnessing the potential of diverse
Fateh Benkhalfallah, Mohamed Ridda Laouar, Mohamed Salah Benkhalfallah   +2 more
doaj   +1 more source

Adaptive Hierarchical Hyper-gradient Descent [PDF]

arXiv, 2020
In this study, we investigate learning rate adaption at different levels based on the hyper-gradient descent framework and propose a method that adaptively learns the optimizer parameters by combining multiple levels of learning rates with hierarchical structures.
arxiv  

Adaptive e-learning environment based on learning styles and its impact on development students' engagement

International Journal of Educational Technology in Higher Education, 2021
Adaptive e-learning is viewed as stimulation to support learning and improve student engagement, so designing appropriate adaptive e-learning environments contributes to personalizing instruction to reinforce learning outcomes.
Hassan A. El-Sabagh
doaj   +1 more source

Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning

Frontiers in Artificial Intelligence, 2021
Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems
Thomas Wilschut, Thomas Wilschut, Florian Sense, Maarten van der Velde, Maarten van der Velde, Zafeirios Fountas, Sarah C. Maaß, Sarah C. Maaß, Sarah C. Maaß, Hedderik van Rijn, Hedderik van Rijn   +10 more
doaj   +1 more source

Enhanced dose prediction for head and neck cancer artificial intelligence‐driven radiotherapy based on transfer learning with limited training data

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Training deep learning dose prediction models for the latest cutting‐edge radiotherapy techniques, such as AI‐based nodal radiotherapy (AINRT) and Daily Adaptive AI‐based nodal radiotherapy (DA‐AINRT), is challenging due to limited data.
Hui‐Ju Wang, Austen Maniscalco, David Sher, Mu‐Han Lin, Steve Jiang, Dan Nguyen   +5 more
wiley   +1 more source

Preconditioned Federated Learning [PDF]

arXiv, 2023
Federated Learning (FL) is a distributed machine learning approach that enables model training in communication efficient and privacy-preserving manner. The standard optimization method in FL is Federated Averaging (FedAvg), which performs multiple local SGD steps between communication rounds.
arxiv  

Does dose calculation algorithm affect the dosimetric accuracy of synthetic CT for MR‐only radiotherapy planning in brain tumors?

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study compares the dosimetric accuracy of deep‐learning‐based MR synthetic CT (sCT) in brain radiotherapy between the Analytical Anisotropic Algorithm (AAA) and AcurosXB (AXB). Additionally, it proposes a novel metric to predict the dosimetric accuracy of sCT for individual post‐surgical brain cases.
Jeffrey C. F. Lui, Francis K. H. Lee, C. C. Law, James C. H. Chow   +3 more
wiley   +1 more source

Adaptive learning and survey data [PDF]

Journal of Economic Behavior & Organization, 2013
This paper investigates the ability of the adaptive learning approach to replicate the expectations of professional forecasters. For a range of macroeconomic and financial variables, we compare constant and decreasing gain learning models to simple, yet powerful benchmark models.
Agnieszka Markiewicz, Agnieszka Markiewicz, Andreas Pick, Andreas Pick   +3 more
openaire   +3 more sources

Non-Adaptive Learning a Hidden Hipergraph [PDF]

arXiv, 2015
We give a new deterministic algorithm that non-adaptively learns a hidden hypergraph from edge-detecting queries. All previous non-adaptive algorithms either run in exponential time or have non-optimal query complexity. We give the first polynomial time non-adaptive learning algorithm for learning hypergraph that asks almost optimal number of queries.
arxiv