In each act or process of knowledge, all components can be classified into two kinds: tacit (implicit) components and focal (explicit) components. This article, first of all introduces the terms of implicit knowledge,...In each act or process of knowledge, all components can be classified into two kinds: tacit (implicit) components and focal (explicit) components. This article, first of all introduces the terms of implicit knowledge, explicit knowledge and their distinctions in the process of English language learning and then provides interactive instruction design to improve learners' communicative competence.展开更多
Three pragmatic theories in terms of two properties of utterance-explicitness and implicitness are surveyed, with a general commentary and a proposal of further development in the study of explicitness and implicitnes...Three pragmatic theories in terms of two properties of utterance-explicitness and implicitness are surveyed, with a general commentary and a proposal of further development in the study of explicitness and implicitness of utterance in view of its sound features.展开更多
We introduce here the concept of Bayesian networks, in compound Poisson model, which provides a graphical modeling framework that encodes the joint probability distribution for a set of random variables within a direc...We introduce here the concept of Bayesian networks, in compound Poisson model, which provides a graphical modeling framework that encodes the joint probability distribution for a set of random variables within a directed acyclic graph. We suggest an approach proposal which offers a new mixed implicit estimator. We show that the implicit approach applied in compound Poisson model is very attractive for its ability to understand data and does not require any prior information. A comparative study between learned estimates given by implicit and by standard Bayesian approaches is established. Under some conditions and based on minimal squared error calculations, we show that the mixed implicit estimator is better than the standard Bayesian and the maximum likelihood estimators. We illustrate our approach by considering a simulation study in the context of mobile communication networks.展开更多
文摘In each act or process of knowledge, all components can be classified into two kinds: tacit (implicit) components and focal (explicit) components. This article, first of all introduces the terms of implicit knowledge, explicit knowledge and their distinctions in the process of English language learning and then provides interactive instruction design to improve learners' communicative competence.
文摘Three pragmatic theories in terms of two properties of utterance-explicitness and implicitness are surveyed, with a general commentary and a proposal of further development in the study of explicitness and implicitness of utterance in view of its sound features.
文摘We introduce here the concept of Bayesian networks, in compound Poisson model, which provides a graphical modeling framework that encodes the joint probability distribution for a set of random variables within a directed acyclic graph. We suggest an approach proposal which offers a new mixed implicit estimator. We show that the implicit approach applied in compound Poisson model is very attractive for its ability to understand data and does not require any prior information. A comparative study between learned estimates given by implicit and by standard Bayesian approaches is established. Under some conditions and based on minimal squared error calculations, we show that the mixed implicit estimator is better than the standard Bayesian and the maximum likelihood estimators. We illustrate our approach by considering a simulation study in the context of mobile communication networks.
