Results 81 to 90 of about 1,863,416 (267)

How is RAN Related to Reading Fluency? A Comprehensive Examination of the Prominent Theoretical Accounts

open access: yesFrontiers in Psychology, 2016
We examined the prominent theoretical explanations of the RAN-reading relationship in a relatively transparent language (Greek) in a sample of children (n= 286) followed from Grade 1 to Grade 2.
TIMOTHY C PAPADOPOULOS   +2 more
doaj   +1 more source

Rapid automatized naming in 6 and 7 years old students [PDF]

open access: yes, 2016
Purpose: to evaluate the speed of RAN in 6- to 7-year-old schoolchildren (1st year of elementary school) and evaluate the difference in Rapid Automatized Naming subtests of colors, letters, numbers and objects.
Araujo   +3 more
core   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

open access: yesAdvanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran   +6 more
wiley   +1 more source

OntOMat: Toward Ontology‐Based Product and Process Design Engineering and Optimization Solutions Fueling Circular Value Chains

open access: yesAdvanced Engineering Materials, EarlyView.
The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ   +19 more
wiley   +1 more source

Bidirectional relationships between phonological processing and basic number knowledge in kindergarten children: a longitudinal study

open access: yesBMC Psychology
An ongoing debate on the association between phonological processing and number knowledge concerns the extent to which they influence each other during early childhood.
Xin Chen   +3 more
doaj   +1 more source

The Naming Commission

open access: yes, 2022
Website documenting the work of the Naming Commission, including their final report and recommendations regarding Department of Defense assets (e.g., names, symbols, displays, monuments, or paraphernalia) that commemorate the efforts of the Confederate ...
United States. Naming Commission.
core  

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

open access: yesAdvanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling   +15 more
wiley   +1 more source

Reading Performance Is Predicted by More Than Phonological Processing

open access: yesFrontiers in Psychology, 2014
We compared three phonological processing components (phonological awareness, rapid automatized naming and phonological memory), verbal working memory, and attention control in terms of how well they predict the various aspects of reading: word ...
Michelle Y. Kibby   +2 more
doaj   +1 more source

The Relationship Between Sustained Attention and Rapid Automatized Naming Tasks [PDF]

open access: yes
Rapid automatized naming (RAN) tasks are potent predictors of reading abilities, butthere is minimal evidence regarding what they specifically measure. In addition, attention is a critical component to cognitive processing and automaticity, factors which
Davenport, Taylor
core  

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

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