Bimesogenic liquid crystals: New materials for high performance flexoelectric and blue phase displays

In this paper we will describe new bimesogenic nematic liquid crystals that have high flexoelectro-optic coefficients (e/K),of the order of 1.5 CN 1 m-1, high switching angles, up to 100° and fast response times, of the order of 100μs or less. We will describe devices constructed, using the ULH texture that may be switched to the optimum angle of 45° for a birefringence based device with the fields of 4Vμm-1 over a wide temperature range. Such devices use an "in plane" optical switching mode, have gray scale capability and a wide viewing angle. We will describe devices using the USH or Grandjean texture that have an optically isotropic "field off" black state, uses "in plane" switching E fields, to give an induced birefringence phase device, with switching times of the order of 20μs. We will briefly describe new highly reflective Blue Phase devices stable over a 50V temperature range in which an electric field is used to switch the reflection from red to green, for example. Full RGB reflections may be obtained with switching times of a few milliseconds. Finally we will briefly mention potential applications including high efficiency RGB liquid crystal laser sources. © 2006 SID.

Fast Hands-free Writing by Gaze Direction

We describe a method for text entry based on inverse arithmetic coding that relies on gaze direction and which is faster and more accurate than using an on-screen keyboard. These benefits are derived from two innovations: the writing task is matched to the capabilities of the eye, and a language model is used to make predictable words and phrases easier to write.

Probabilistic inference for fast learning in control

A novel framework is provided for very fast model-based reinforcement learning in continuous state and action spaces. It requires probabilistic models that explicitly characterize their levels of condence. Within the framework, exible, non-parametric models are used to describe the world based on previously collected experience. It demonstrates learning on the cart-pole problem in a setting where very limited prior knowledge about the task has been provided. Learning progressed rapidly, and a good policy found after only a small number of iterations.