Enhanced Linguistic Computational Models and Their similarity with Yager’s Computing with Words

2021 ◽  
Author(s):  
Prashant K. Gupta ◽  
Deepak Sharma ◽  
Javier Andreu-Perez
Keyword(s):  
Computational Models ◽  
Computing With Words

Sequential Difficulty Effects During Strategy Execution

2012 ◽  
Vol 59 (5) ◽  
pp. 295-301 ◽  
Author(s):  
Kim Uittenhove ◽  
Patrick Lemaire
Keyword(s):  
Computational Models ◽  
Preceding Trial ◽  
Human Cognition ◽  
Strategy Execution ◽  
Strategy Performance ◽  
Empirical Implications

In two experiments, we tested the hypothesis that strategy performance on a given trial is influenced by the difficulty of the strategy executed on the immediately preceding trial, an effect that we call strategy sequential difficulty effect. Participants’ task was to provide approximate sums to two-digit addition problems by using cued rounding strategies. Results showed that performance was poorer after a difficult strategy than after an easy strategy. Our results have important theoretical and empirical implications for computational models of strategy choices and for furthering our understanding of strategic variations in arithmetic as well as in human cognition in general.

Does Viotin Activate Violin More Than Viocin?

2014 ◽  
Vol 61 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Manuel Perea ◽  
Victoria Panadero
Keyword(s):  
Word Recognition ◽  
Visual Word Recognition ◽  
Developmental Dyslexia ◽  
Computational Models ◽  
Error Rates ◽  
Visual Word ◽  
Base Word ◽  
Similar Response ◽  
Skilled Readers ◽  
Young Readers

The vast majority of neural and computational models of visual-word recognition assume that lexical access is achieved via the activation of abstract letter identities. Thus, a word’s overall shape should play no role in this process. In the present lexical decision experiment, we compared word-like pseudowords like viotín (same shape as its base word: violín) vs. viocín (different shape) in mature (college-aged skilled readers), immature (normally reading children), and immature/impaired (young readers with developmental dyslexia) word-recognition systems. Results revealed similar response times (and error rates) to consistent-shape and inconsistent-shape pseudowords for both adult skilled readers and normally reading children – this is consistent with current models of visual-word recognition. In contrast, young readers with developmental dyslexia made significantly more errors to viotín-like pseudowords than to viocín-like pseudowords. Thus, unlike normally reading children, young readers with developmental dyslexia are sensitive to a word’s visual cues, presumably because of poor letter representations.

Computational Models of Scientific Discovery: Do They Compute?

1989 ◽  
Vol 34 (10) ◽  
pp. 895-897 ◽  
Author(s):  
Robert J. Sternberg
Keyword(s):  
Computational Models ◽  
Scientific Discovery

Computational Models of Self-Regulation: Innovations in Theory Development and Testing

2012 ◽  
Author(s):  
Jeffrey B. Vancouver ◽  
Justin M. Weinhardt ◽  
Paul J. Hanges
Keyword(s):  
Computational Models ◽  
Self Regulation ◽  
Theory Development

Effects of Task Performance and Task Complexity on the Validity of Computational Models of Attention

2008 ◽  
Author(s):  
Lisette de Koning ◽  
Peter-Paul van Maanen ◽  
Kees van Dongen
Keyword(s):  
Task Performance ◽  
Computational Models ◽  
Task Complexity ◽  
And Task

Modeling fine particles and alkali metal compound behavior in a kraft recovery boiler

TAPPI Journal ◽  
2012 ◽  
Vol 11 (7) ◽  
pp. 9-14 ◽  
Author(s):  
AINO LEPPÄNEN ◽  
ERKKI VÄLIMÄKI ◽  
ANTTI OKSANEN
Keyword(s):  
Alkali Metal ◽  
Computational Models ◽  
Fine Particles ◽  
Black Liquor ◽  
Melting Behavior ◽  
Metal Compound ◽  
Effect Of Temperature ◽  
Particle Model ◽  
Boiler Furnace ◽  
Recovery Boiler

Under certain conditions, ash in black liquor forms a locally corrosive environment in a kraft recovery boiler. The ash also might cause efficiency losses and even boiler shutdown because of plugging of the flue gas passages. The most troublesome compounds in a fuel such as black liquor are potassium and chlorine because they change the melting behavior of the ash. Fouling and corrosion of the kraft recovery boiler have been researched extensively, but few computational models have been developed to deal with the subject. This report describes a computational fluid dynamics-based method for modeling the reactions between alkali metal compounds and for the formation of fine fume particles in a kraft recovery boiler furnace. The modeling method is developed from ANSYS/FLUENT software and its Fine Particle Model extension. We used the method to examine gaseous alkali metal compound and fine fume particle distributions in a kraft recovery boiler furnace. The effect of temperature and the boiler design on these variables, for example, can be predicted with the model. We also present some preliminary results obtained with the model. When the model is developed further, it can be extended to the superheater area of the kraft recovery boiler. This will give new insight into the variables that increase or decrease fouling and corrosion

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