• Language and Information
• /
• v.9 no.1
• /
• pp.51-68
• /
• 2005

This paper proposes an informational approach to the dative alternation in English following up on the Stochastic Optimality- Theoretic (OT) model by Bresnan and Nikitina (2003). While Bresnan and Nikitina's stochastic OT model resolves the crucial problem of 'gradience' unavoidably implicated in variation phenomena by applying the notion of probability to linguistic problems, it fails to account for the details of the unusually alternating examples, which normally would not alternate. More importantly, it fails to capture the focus effect involved in the alternation. This paper has worked out all the problematic examples by modifying the Bresnan and Nikitina model. This new account captures not only the unusual behavior of the less-alternating verbs and idioms but also the special focus effect of the common alternating verbs.

• Language and Information
• /
• v.11 no.1
• /
• pp.77-96
• /
• 2007

This paper investigates syntactic variations in English such as Dative Alternation, Particle Inversion, and Object Postposition (Heavy NP Shift) within the framework of Optimality Theory, and shows that the same set of morphological, informational, and processing constraints affect all these variations. In particular, it shows that the variants that used to be regarded as ungrammatical are in fact used fairly often in reality, especially when processing or informational conditions are met, and therefore, grammatical judgment may not be always categorical but sometimes gradient. It is argued that the notion of distance in constraint ranking in stochastic OT can effectively explain the gradience and variability of grammaticality in the variation phenomena.

• Journal of Korea Water Resources Association
• /
• v.33 no.3
• /
• pp.331-340
• /
• 2000

This study aims to develop a methodology of real time forecasting of mundation risk based on DAMBRK model and Kalman filter. The model is based on implicit, nonlinear finite difference approximatIons of the one-dimensional dynamic wave equations. The stochastic estimator uses on extended Kalman filter to provide optimal updating estimates. These are accomplished by combining the predictions of the determurustic model with real time observauons modified by the Kalman filter gain ractor. Inundation risks are also estimated by applying Monte Carlo simulation to consider the variability in cross section geometry and Manning's roughness coefficient. The model calibrated by applying to the floods ot South Han River on September, 1990 and August, 1995. The Kalman tilter model indicates that significant improvement compared to deteriministic analysis in flood routing predictions in the river. Overtopping risk of levee is also presented by comparing levee height with simulated flood level. level.