Behaviorism

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Educación Tecnología Salud y medicina

BEHAVIORISM Uriel Tellez Shu-chuan Chuang Marlene Chiquil Janet Uh Tonatiuh Miravete Harif Caro

Behavioral Approach in Language ,[object Object]

Method of Learning ,[object Object],[object Object],[object Object],[object Object]

Stimulus-Response Action ,[object Object]

Reinforcement ,[object Object],[object Object],[object Object]

Classical Conditioning ,[object Object],[object Object],[object Object]

Operant Conditioning ,[object Object],[object Object],[object Object],[object Object]

Markov Models of Sentences ,[object Object],[object Object],[object Object]

Imitation ,[object Object],[object Object],[object Object]

Supporting Evidence ,[object Object],[object Object],[object Object],[object Object]

Contrary Evidence ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Conclusion ,[object Object],[object Object]

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language learning : It is the result of direct instruction in the rules of language And it certainly is not an age-appropriate activity for young learners. In language learning, students have conscious knowledge of the new language and can talk about that knowledge. They can fill in the blanks on a grammar page. language acquisition : Children acquire language through a subconscious process during which they are unaware of grammatical rules. They readily acquire the language to communicate with friends. In order to acquire language, the learner needs a source of natural communication. The emphasis is on the text of the communication and not on the form. Young students who are in the process of acquiring English get plenty of “on the job” practice.

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Language, Language Acquisition, Language Learning, Second Language,Bilingualism, Child Language, Linguistics,Hypothesis, Noam Chomsky (Cognitive Generative Quantitative Functional theories of grammar Phonology Morphology Morphophonology Syntax Lexis Semantics Pragmatics Graphemics Orthography Semiotics) (Anthropological Comparative Historical Etymology Graphetics Phonetics Sociolinguistics) (Computational Contrastive Evolutionary Forensic Internet Language acquisition Second-language acquisition Language assessment Language development Language education Linguistic anthropology Neurolinguistics Psycholinguistics) (History of linguistics Linguistic prescription List of linguists Unsolved linguistics problems)

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Poster to be presented at Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2024, Kaust, Saudi Arabia, https://cemse.kaust.edu.sa/stochnum/events/event/snsl-workshop-2024. In this work we have considered a setting that mimics the Henry problem \cite{Simpson2003,Simpson04_Henry}, modeling seawater intrusion into a 2D coastal aquifer. The pure water recharge from the ``land side'' resists the salinisation of the aquifer due to the influx of saline water through the ``sea side'', thereby achieving some equilibrium in the salt concentration. In our setting, following \cite{GRILLO2010}, we consider a fracture on the sea side that significantly increases the permeability of the porous medium. The flow and transport essentially depend on the geological parameters of the porous medium, including the fracture. We investigated the effects of various uncertainties on saltwater intrusion. We assumed uncertainties in the fracture width, the porosity of the bulk medium, its permeability and the pure water recharge from the land side. The porosity and permeability were modeled by random fields, the recharge by a random but periodic intensity and the thickness by a random variable. We calculated the mean and variance of the salt mass fraction, which is also uncertain. The main question we investigated in this work was how well the MLMC method can be used to compute statistics of different QoIs. We found that the answer depends on the choice of the QoI. First, not every QoI requires a hierarchy of meshes and MLMC. Second, MLMC requires stable convergence rates for $\EXP{g_{\ell} - g_{\ell-1}}$ and $\Var{g_{\ell} - g_{\ell-1}}$. These rates should be independent of $\ell$. If these convergence rates vary for different $\ell$, then it will be hard to estimate $L$ and $m_{\ell}$, and MLMC will either not work or be suboptimal. We were not able to get stable convergence rates for all levels $\ell=1,\ldots,5$ when the QoI was an integral as in \eqref{eq:integral_box}. We found that for $\ell=1,\ldots 4$ and $\ell=5$ the rate $\alpha$ was different. Further investigation is needed to find the reason for this. Another difficulty is the dependence on time, i.e. the number of levels $L$ and the number of sums $m_{\ell}$ depend on $t$. At the beginning the variability is small, then it increases, and after the process of mixing salt and fresh water has stopped, the variance decreases again. The number of random samples required at each level was estimated by calculating the decay of the variances and the computational cost for each level. These estimates depend on the minimisation function in the MLMC algorithm. To achieve the efficiency of the MLMC approach presented in this work, it is essential that the complexity of the numerical solution of each random realisation is proportional to the number of grid vertices on the grid levels.

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1. BEHAVIORISM Uriel Tellez Shu-chuan Chuang Marlene Chiquil Janet Uh Tonatiuh Miravete Harif Caro

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Behaviorism

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