Density control of ZnO nanowires grown using Au-PMMA nanoparticles and their growth behavior.

Au nanoparticles stabilized by poly(methyl methacrylate) (PMMA) were used as a catalyst to grow vertically aligned ZnO nanowires (NWs). The density of ZnO NWs with very uniform diameter was controlled by changing the concentration of Au-PMMA nanoparticles (NPs). The density was in direct proportion to the concentration of Au-PMMA NPs. Furthermore, the growth process of ZnO NWs using Au-PMMA NPs was systematically investigated through comparison with that using Au thin film as a catalyst. Au-PMMA NPs induced polyhedral-shaped bases of ZnO NWs separated from each other, while Au thin film formed a continuous network of bases of ZnO NWs. This approach provides a facile and cost-effective catalyst density control method, allowing us to grow high-quality vertically aligned ZnO NWs suitable for many viable applications.

Probabilistic graphical models for semi-supervised traffic classification

Traffic classification using machine learning continues to be an active research area. The majority of work in this area uses off-the-shelf machine learning tools and treats them as black-box classifiers. This approach turns all the modelling complexity into a feature selection problem. In this paper, we build a problem-specific solution to the traffic classification problem by designing a custom probabilistic graphical model. Graphical models are a modular framework to design classifiers which incorporate domain-specific knowledge. More specifically, our solution introduces semi-supervised learning which means we learn from both labelled and unlabelled traffic flows. We show that our solution performs competitively compared to previous approaches while using less data and simpler features. Copyright © 2010 ACM.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

Strong flexoelectric behavior in bimesogenic liquid crystals

In this paper, we demonstrate strong flexoelectric coupling in bimesogenic liquid crystals. This strong coupling is determined via the flexoelectro-optic effect in chiral nematic liquid crystals based on bimesogenic mixtures that are doped with low concentrations of high twisting power chiral additive. Two mixtures were examined: one had a pitch length of p∼300nm, the other had a pitch length of p∼600nm. These mixtures exhibit enantiotropic chiral nematic phases close to room temperature. We found that full-intensity modulation, that is, a rotation of the optic axis of 45° between crossed polarizers, could be achieved at significantly lower applied electric fields (E<5Vμm -1) than previously reported. In fact, for the condition of full-intensity modulation, the lowest electric-field strength recorded was E=2Vμm-1. As a result of a combination of the strong flexoelectric coupling and a divergence in the pitch, tilt angles of the optic axis up to 87°, i.e., a rotation of the optic axis through 174°, were observed. Furthermore, the flexoelastic ratios, which may be considered as a figure-of-merit parameter, were calculated from the results and found to be large, ranging from 1.3to2C/Nm for a temperature range of up to 40°C. © 2006 American Institute of Physics.

Instability in threshold voltage and subthreshold behavior in Hf-In-Zn-O thin film transistors induced by bias-and light-stress

Electrical bias and light stressing followed by natural recovery of amorphous hafnium-indium-zinc-oxide (HIZO) thin film transistors with a silicon oxide/nitride dielectric stack reveals defect density changes, charge trapping and persistent photoconductivity (PPC). In the absence of light, the polarity of bias stress controls the magnitude and direction of the threshold voltage shift (Δ VT), while under light stress, VT consistently shifts negatively. In all cases, there was no significant change in field-effect mobility. Light stress gives rise to a PPC with wavelength-dependent recovery on time scale of days. We observe that the PPC becomes more pronounced at shorter wavelengths. © 2010 American Institute of Physics.