A Multi-level Model for Recognition of Intonation Labels

1997 ◽  
pp. 291-308 ◽  
Author(s):  
M. Ostendorf ◽  
K. Ross
Keyword(s):  
Level Model ◽  
Multi Level

An Analysis on Factors of Parent Involvement in Middle School Using Multi-Level Model

2018 ◽  
Vol 18 (5) ◽  
pp. 521-540
Author(s):  
Eunyoung Kim ◽  
◽  
Soonbum Kwon ◽  
Meejung Chin ◽  
◽  
...  
Keyword(s):  
Middle School ◽  
Parent Involvement ◽  
Level Model ◽  
Multi Level

scholarly journals A Network Analysis of the Relationship among Reading, Spelling and Maths Skills

2021 ◽  
Vol 11 (5) ◽  
pp. 656
Author(s):  
Pierluigi Zoccolotti ◽  
Paola Angelelli ◽  
Chiara Valeria Marinelli ◽  
Daniele Luigi Romano
Keyword(s):  
Network Analysis ◽  
Clinical Analysis ◽  
Skill Learning ◽  
Fifth Grade ◽  
Learning Skills ◽  
Level Model ◽  
Multi Level ◽  
Unselected Group ◽  
The Relationship

Background. Skill learning (e.g., reading, spelling and maths) has been predominantly treated separately in the neuropsychological literature. However, skills (as well as their corresponding deficits), tend to partially overlap. We recently proposed a multi-level model of learning skills (based on the distinction among competence, performance, and acquisition) as a framework to provide a unitary account of these learning skills. In the present study, we examined the performance of an unselected group of third- to fifth-grade children on standard reading, spelling, and maths tasks, and tested the relationships among these skills with a network analysis, i.e., a method particularly suited to analysing relations among different domains. Methods. We administered a battery of reading, spelling, and maths tests to 185 third-, fourth-, and fifth-grade children (103 M, 82 F). Results. The network analysis indicated that the different measures of the same ability (i.e., reading, spelling, and maths) formed separate clusters, in keeping with the idea that they are based on different competences. However, these clusters were also related to each other, so that three nodes were more central in connecting them. In keeping with the multi-level model of learning skills, two of these tests (arithmetic facts subtest and spelling words with ambiguous transcription) relied heavily on the ability to recall specific instances, a factor hypothesised to underlie the co-variation among learning skills. Conclusions. The network analysis indicated both elements of association and of partial independence among learning skills. Interestingly, the study was based on standard clinical instruments, indicating that the multi-level model of learning skills might provide a framework for the clinical analysis of these learning skills.

A Multi‐Level Model of I‐deals in Workgroups: Employee and Coworker Perceptions of Leader Fairness, I‐Deals and Group Performance

2021 ◽  
Author(s):  
Smriti Anand ◽  
Jeremy D. Meuser ◽  
Prajya R. Vidyarthi ◽  
Robert C. Liden ◽  
Denise M. Rousseau ◽  
...  
Keyword(s):  
Group Performance ◽  
Level Model ◽  
Multi Level

Framing Climate Change: A Multi-level Model

2017 ◽  
pp. 215-271 ◽  
Author(s):  
Renée Moernaut ◽  
Jelle Mast ◽  
Luc Pauwels
Keyword(s):  
Climate Change ◽  
Level Model ◽  
Multi Level

scholarly journals An organ-based multi-level model for glucose homeostasis: organ distributions, timing, and impact of blood flow

2020 ◽  
Author(s):  
Tilda Herrgårdh ◽  
Hao Li ◽  
Elin Nyman ◽  
Gunnar Cedersund
Keyword(s):  
Blood Flow ◽  
Glucose Homeostasis ◽  
Statistical Tests ◽  
Cellular Level ◽  
Whole Body ◽  
Response Curves ◽  
Future Data ◽  
Level Model ◽  
Multi Level ◽  
Original Cell

AbstractGlucose homeostasis is the tight control of glucose in the blood. This complex control is important and not yet sufficiently understood, due to its malfunction in serious diseases like diabetes. Due to the involvement of numerous organs and sub-systems, each with their own intra-cellular control, we have developed a multi-level mathematical model, for glucose homeostasis, which integrates a variety of data. Over the last 10 years, this model has been used to insert new insights from the intra-cellular level into the larger whole-body perspective. However, the original cell-organ-body translation has during these years never been updated, despite several critical shortcomings, which also have not been resolved by other modelling efforts. For this reason, we here present an updated multi-level model. This model provides a more accurate sub-division of how much glucose is being taken up by the different organs. Unlike the original model, we now also account for the different dynamics seen in the different organs. The new model also incorporates the central impact of blood flow on insulin-stimulated glucose uptake. Each new improvement is clear upon visual inspection, and they are also supported by statistical tests. The final multi-level model describes >300 data points in >40 time-series and dose-response curves, resulting from a large variety of perturbations, describing both intra-cellular processes, organ fluxes, and whole-body meal responses. We hope that this model will serve as an improved basis for future data integration, useful for research and drug developments within diabetes.

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