Nanoelectromechanical DRAM for ultra-large-scale integration (ULSI)

A Nanoelectromechanical (NEM) device developed for dynamic random access memory (DRAM) is reported. A vertical nanotube structure is employed to form the electromechanical switch and capacitor structure. The mechanical movement of the nanotube defines 'On' and 'OFF' states and the electrical signals which result lead to charge storage in a vertical capacitor structure as in a traditional DRAM. The vertical structure contributes greatly to a decrease in cell dimension. The main concept of the NEM switch and capacitor can be applied to other memory devices as well. © 2005 IEEE.

Time-resolved volumetric measurement of fine-scale coherent structures in turbulence.

We present full volumetric (three-dimensional) time-resolved (+one-dimensional) measurements of the velocity field in a large water mixing tank, allowing us to assess spatial and temporal rotational energy (enstrophy) and turbulent energy dissipation intermittency. In agreement with previous studies, highly intermittent behavior is observed, with intense coherent flow structures clustering in the periphery of larger vortices. However, further to previous work the full volumetric measurements allow us to separate out the effects of advection from other effects, elucidating not only their topology but also the evolution of these intense events, through the local balance of stretching and diffusion. These findings contribute toward a better understanding of the intermittency phenomenon, which should pave the way for more accurate models of the small-scale motions based on an understanding of the underlying flow physics.

Observation of large-scale features on graphite by scanning tunnelling microscopy

Superlattice structures and rippling fringes were imaged on two separate pieces of graphite (HOPG) by scanning tunnelling microscopy (STM). We observed the corrugation conservation phenomenon on one of the superlattice structures where an overlayer does not attenuate the corrugation amplitude of the superlattice. Such a phenomenon may illustrate an implication that nanoscale defects a few layers underneath the surface may propagate through many layers without decay and form the superlattice structure on the topmost surface. Some rippling fringes with periodicities of 20 nm and 30 nm and corrugations of 0.1 nm and 0.15nm were observed in the superlattice area and in nearby regions. Such fringes are believed to be due to physical buckling of the surface. The stress required to generate such structures is estimated, and a possible cause is discussed. An equation relating the attenuation factor to the number of overlayers is proposed. © 2005 The Japan Society of Applied Physics.

Detection of large-scale concrete columns for automated bridge inspection

There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame. This is because manually inspecting bridges is a time-consuming and costly task, and some state Departments of Transportation (DOT) cannot afford the essential costs and manpower. In this paper, a novel method that can detect large-scale bridge concrete columns is proposed for the purpose of eventually creating an automated bridge condition assessment system. The method employs image stitching techniques (feature detection and matching, image affine transformation and blending) to combine images containing different segments of one column into a single image. Following that, bridge columns are detected by locating their boundaries and classifying the material within each boundary in the stitched image. Preliminary test results of 114 concrete bridge columns stitched from 373 close-up, partial images of the columns indicate that the method can correctly detect 89.7% of these elements, and thus, the viability of the application of this research.

Large Scale Column Detection for Bridge Inspection

Manually inspecting bridges is a time-consuming and costly task. There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame as some state DOTs cannot afford the essential costs and manpower. This paper presents a novel method that can detect bridge concrete columns from visual data for the purpose of eventually creating an automated bridge condition assessment system. The method employs SIFT feature detection and matching to find overlapping areas among images. Affine transformation matrices are then calculated to combine images containing different segments of one column into a single image. Following that, the bridge columns are detected by identifying the boundaries in the stitched image and classifying the material within each boundary. Preliminary test results using real bridge images indicate that most columns in stitched images can be correctly detected and thus, the viability of the application of this research.

Uncertainty management for on-line optimisation of a POMDP-based large-scale spoken dialogue system

The optimization of dialogue policies using reinforcement learning (RL) is now an accepted part of the state of the art in spoken dialogue systems (SDS). Yet, it is still the case that the commonly used training algorithms for SDS require a large number of dialogues and hence most systems still rely on artificial data generated by a user simulator. Optimization is therefore performed off-line before releasing the system to real users. Gaussian Processes (GP) for RL have recently been applied to dialogue systems. One advantage of GP is that they compute an explicit measure of uncertainty in the value function estimates computed during learning. In this paper, a class of novel learning strategies is described which use uncertainty to control exploration on-line. Comparisons between several exploration schemes show that significant improvements to learning speed can be obtained and that rapid and safe online optimisation is possible, even on a complex task. Copyright © 2011 ISCA.