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Lexical chains provide a representation of the lexical cohesion structure of a text. In this paper , we propose two lexical chain based cohesion models to incorporate lexical cohesion into document-level statistical machine translation: 1) a count cohesion model that rewards a hypothesis whenever a chain word occurs in the hypothesis, 2) and a probability(More)
A previous study of a sand-swimming lizard, the sandfish, revealed that it swims within granular media at speeds up to 0.4 body-lengths/cycle using body undulations (approximately a single period sinusoidal traveling wave) without limb use. Inspired by the organism, we develop a numerical model of a robot swimming in a simulated granular medium to guide the(More)
In the present paper, we consider list decoding for both random rank metric codes and random linear rank metric codes. Firstly, we show that, for arbitrary 0 < R < 1 and > 0 (and R are independent), if 0 < n m ≤ , then with high probability a random rank metric code in F m×n q of rate R can be list-decoded up to a fraction (1−R−) of rank errors with(More)
In parallel to the changes in both the architecture domain – the move toward chip multiprocessors (CMPs) – and the application domain – the move toward increasingly data-intensive workloads – issues such as performance, energy efficiency and CPU availability are becoming increasingly critical. The CPU availability can change dynamically due to several(More)
— Previous study of a sand-swimming lizard, the sandfish, Scincus scincus, revealed that the animal swims within granular media at speeds up to 0.4 body-lengths/cycle using body undulation (approximately a single period sinusoidal traveling wave) without limb use [1]. Inspired by this biological experiment and challenged by the absence of robotic devices(More)
— Previously we modeled the undulatory subsurface locomotion of the sandfish lizard with a sand-swimming robot which displayed performance comparable to the organism. In this work we control the lift forces on the robot by varying its head shape and demonstrate that these granular forces predict the vertical motion of the robot. Inspired by the tapered head(More)