Best basis-based intelligent machine fault diagnosis

The wavelet packet transform decomposes a signal into a set of bases for time–frequency analysis. This decomposition creates an opportunity for implementing distributed data mining where features are extracted from different wavelet packet bases and served as feature vectors for applications. This paper presents a novel approach for integrated machine fault diagnosis based on localised wavelet packet bases of vibration signals. The best basis is firstly determined according to its classification capability. Data mining is then applied to extract features and local decisions are drawn using Bayesian inference. A final conclusion is reached using a weighted average method in data fusion. A case study on rolling element bearing diagnosis shows that this approach can greatly improve the accuracy ofdiagno sis.

Rapid displacement of dengue virus type 1 by type 4, Pacific region, 2007-2009

Since 2000-2001, dengue virus type 1 has circulated in the Pacific region. However, in 2007, type 4 reemerged and has almost completely displaced the strains of type 1. If only 1 serotype circulates at any time and is replaced approximately every 5 years, DENV-3 may reappear in 2012.

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.

Identification of a cryptic Prokaryotic promoter within the cDNA encoding the 5′ End of Dengue Virus RNA Genome

Infectious cDNA clones of RNA viruses are important research tools, but flavivirus cDNA clones have proven difficult to assemble and propagate in bacteria. This has been attributed to genetic instability and/or host cell toxicity, however the mechanism leading to these difficulties has not been fully elucidated. Here we identify and characterize an efficient cryptic bacterial promoter in the cDNA encoding the dengue virus (DENV) 5′ UTR. Following cryptic transcription in E. coli, protein expression initiated at a conserved in-frame AUG that is downstream from the authentic DENV initiation codon, yielding a DENV polyprotein fragment that was truncated at the N-terminus. A more complete understanding of constitutive viral protein expression in E. coli might help explain the cloning and propagation difficulties generally observed with flavivirus cDNA.

A nanoscratch method for measuring hardness of thin films

Thin solid films were extensively used in the making of solar cells, cutting tools, magnetic recording devices, etc. As a result, the accurate measurement of mechanical properties of the thin films, such as hardness and elastic modulus, was required. The thickness of thin films normally varies from tens of nanometers to several micrometers. It is thus challenging to measure their mechanical properties. In this study, a nanoscratch method was proposed for hardness measurement. A three-dimensional finite element method (3-D FEM) model was developed to validate the nanoscratch method and to understand the substrate effect during nanoscratch. Nanoindentation was also used for comparison. The nanoscratch method was demonstrated to be valuable for measuring hardness of thin solid films.

Hydrogen gas sensing performance of a Pt/graphene/SiC device

In this work, we present the development of a Pt/graphene/SiC device for hydrogen gas sensing. A single layer of graphene was deposited on 6H-SiC via chemical vapor deposition. The presence of graphene C-C bonds was observed via X-ray photoelectron spectroscopy analysis. Current-voltage characteristics of the device were measured at the presence of hydrogen at different temperatures, from 25°C to 170°C. The dynamic response of the device was recorded towards hydrogen gas at an optimum temperature of 130°C. A voltage shift of 191 mV was recorded towards 1% hydrogen at −1 mA constant current.