p-MOS controlled lateral thyristor: A MOS controllable thyristor suitable for integration

A novel CMOS compatible lateral thyristor is proposed in this paper. Its thyristor conduction is fully controlled by a p-MOS gate. Loss of MOS control due to parasitic latch-up has been eliminated and triggering of the main thyristor at lower forward current achieved. The device operation has been verified by 2-D numerical simulations and experimental fabrication.

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.

Discovering transcriptional modules by Bayesian data integration.

MOTIVATION: We present a method for directly inferring transcriptional modules (TMs) by integrating gene expression and transcription factor binding (ChIP-chip) data. Our model extends a hierarchical Dirichlet process mixture model to allow data fusion on a gene-by-gene basis. This encodes the intuition that co-expression and co-regulation are not necessarily equivalent and hence we do not expect all genes to group similarly in both datasets. In particular, it allows us to identify the subset of genes that share the same structure of transcriptional modules in both datasets. RESULTS: We find that by working on a gene-by-gene basis, our model is able to extract clusters with greater functional coherence than existing methods. By combining gene expression and transcription factor binding (ChIP-chip) data in this way, we are better able to determine the groups of genes that are most likely to represent underlying TMs. AVAILABILITY: If interested in the code for the work presented in this article, please contact the authors. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Materials and devices toward three-dimensional integration

It has been shown that the apparent benefits of a two-layer stacked SOI system, i.e. packing density and speed improvements, are less than could be expected in the context of a VLSI requirement [1]. In this project the stacked SOI system has been identified as having major application in the realization of integrated, mixed technology systems. Zone-melting-recrystallization (ZMR) with lasers and electron beams have been used to produce device quality SOI material and a small test-bed circuit has been designed as a demonstration of the feasibility of this approach. © 1988.

The use of syntax and multiple alternatives in the VODIS voice operated database inquiry system

The paper describes the architecture of VODIS, a voice operated database inquiry system, and presents some experiments which investigate the effects on performance of varying the level of a priori syntactic constraints. The VODIS system includes a novel mechanism for incorporating context-free grammatical constraints directly into the word recognition algorithm. This allows the degree of a priori constraint to be smoothly varied and provides for the controlled generation of multiple alternatives. The results show that when the spoken input deviates from the predefined task grammar, a combination of weak a priori syntax rules in conjunction with full a posteriori parsing on a lattice of alternative word matches provides the most robust recognition performance. © 1991.

Continuous speech recognition for the TIMIT database using neural networks

Four types of neural networks which have previously been established for speech recognition and tested on a small, seven-speaker, 100-sentence database are applied to the TIMIT database. The networks are a recurrent network phoneme recognizer, a modified Kanerva model morph recognizer, a compositional representation phoneme-to-word recognizer, and a modified Kanerva model morph-to-word recognizer. The major result is for the recurrent net, giving a phoneme recognition accuracy of 57% from the si and sx sentences. The Kanerva morph recognizer achieves 66.2% accuracy for a small subset of the sa and sx sentences. The results for the word recognizers are incomplete.

MMI training for continuous phoneme recognition on the TIMIT database

This paper reports our experiences with a phoneme recognition system for the TIMIT database which uses multiple mixture continuous density monophone HMMs trained using MMI. A comprehensive set of results are presented comparing the ML and MMI training criteria for both diagonal and full covariance models. These results using simple monophone HMMs show clear performance gains achieved by MMI training, and are comparable to the best reported by others including those which use context-dependent models. In addition, the paper discusses a number of performance and implementation issues which are crucial to successful MMI training.