836 research outputs found
Fuzzy Bayesian inference
Bayesian methods provide formalism for reasoning about partial beliefs under conditions of uncertainty. Given a set of exhaustive and mutually exclusive hypotheses, one can compute the probability of a hypothesis for a given evidence using the Bayesian inversion formula. In Bayesian's inference, the evidence could be a single atomic proposition or multi-valued one. For the multi-valued evidence, these values could be discrete, continuous, or fuzzy. For the continuous-valued evidence, the density functions used in the Bayesian inference are difficult to be determined in many practical situations. Complicated laboratory testing and advance statistical techniques are required to estimate the parameters of the assumed type of distribution. Using the proposed fuzzy Bayesian approach, a formulation is derived to estimate the density function from the conditional probabilities of the fuzzy-supported values. It avoids the complicated testing and analysis, and it does not require the assumption of a particular type of distribution. The estimated density function in our approach is proved to conform to two axioms in the theorem of probability. Example is provided in the paper.published_or_final_versio
CONTENT
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Selective Stimulability in the Speech and Language Assessment of Bilingual Children with Selective Mutism
English Language Learners (ELLs) with Selective Mutism (SM) mirror their typically developing, bilingual peers who are going through the silent period. The silent period is a normal phenomenon characterized by decreased expressive language and a general lack of communication that is temporary. Understanding second language acquisition and differentiating SM from the silent period, however, is critical to reduce over- and under-identification of children for services. Whereas bilingual children with SM do not speak in either of their languages, bilingual children in the silent period are only silent in their second language. Although limited information exists regarding assessment and treatment for SM in ELLs, general assessment and intervention strategies are available. The notion of selective stimulability (how stimulable a child with SM is for expressive communication) may be used in assessment in order to encourage children with SM to communicate expressively when using speech and language protocols and for determining prognosis for treatment. Guidelines for differential diagnosis of SM and the silent period are offered in this paper, including a case example of the use of selective stimulability in a speech-language assessment of a Spanish-speaking child. Moreover, additional information related to the assessment process and implications for intervention are provided
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