Correlation between density of states distributions and the fermi level position in interfacial regions of amorphous silicon thin film transistors

This paper investigates the variation of the integrated density of states with conduction activation energy in hydrogenated amorphous silicon thin film transistors. Results are given for two different gate insulator layers, PECVD silicon oxide and thermally grown silicon dioxide. The different gate insulators produce transistors with very different initial transfer characteristics, but the variation of integrated density of states with conduction activation energy is shown to be similar.

Bayesian approach to signal modelling

In this paper, an introduction to Bayesian methods in signal processing will be given. The paper starts by considering the important issues of model selection and parameter estimation and derives analytic expressions for the model probabilities of two simple models. The idea of marginal estimation of certain model parameter is then introduced and expressions are derived for the marginal probability densities for frequencies in white Gaussian noise and a Bayesian approach to general changepoint analysis is given. Numerical integration methods are introduced based on Markov chain Monte Carlo techniques and the Gibbs sampler in particular.

Technique for wavelength converting a 2.488 Gb/s signal whilst simultaneously monitoring and replacing a wavelength identifying pilot tone

A wavelength conversion device was demonstrated at the bit rate of 2.488 Gb/s with 2R (reamplification and reshaping) regenerative properties. A low frequency pilot tone was removed during the conversion process and a new one added. The wavelength converter is shown to operate well at 10 Gb/s, and tone identification/replacement should also be possible at this data rate.

Quality enhancement of a WDM signal using dispersion-imbalanced loop mirror

The nonlinear filtering of a 10Gb/s data stream in a dispersion-imbalanced fibre loop mirror has been demonstrated over a wide spectral range of 28nm. A relative extinction ratio of - 30 dB for the cw background has been achieved across the whole spectral range.

Blind frequency synchronisation for OFDM systems with pulse shaping

In multi-carrier systems, small carrier frequency offsets result in significant degradation of performance and this offset should be compensated before demodulation can be performed. In this paper, we consider a generic multi-carrier system with pulse shaping and estimate the frequency offset by exploiting the cyclostationarity of the received signal. By transforming the time domain signal to the cyclic correlation domain we are able to estimate the frequency offset without the aid of pilot symbols or the cyclic prefix. The Bayesian framework is used to obtain the estimate and we show how we can simplify the estimation process. © 1999 IEEE.

The Bayesian Approach to Signal Modelling

In this paper, an introduction to Bayesian methods in signal processing will be given. The paper starts by considering the important issues of model selection and parameter estimation and derives analytic expressions for the model probabilities of two simple models. The idea of marginal estimation of certain model parameter is then introduced and expressions are derived for the marginal probabilitiy densities for frequencies in white Gaussian noise and a Bayesian approach to general changepoint analysis is given. Numerical integration methods are introduced based on Markov chain Monte Carlo techniques and the Gibbs sampler in particular.

Molecular evolution of CXCR1, a G protein-coupled receptor involved in signal transduction of neutrophils

Human neutrophils are a type of white blood cell, which forms an early line of defense against bacterial infections. Neutrophils are highly responsive to the chemokine, interleukin-8 (IL-8) due to the abundant distribution of CXCR1, one of the IL-8 receptors on the neutrophil cell surface. As a member of the GPCR family, CXCR1 plays a crucial role in the IL-8 signal transduction pathway in neutrophils. We sequenced the complete coding region of the CXCR1 gene in worldwide human populations and five representative nonhuman primate species. Our results indicate accelerated protein evolution in the human lineage, which was likely caused by Darwinian positive selection. The sliding window analysis and the codon-based neutrality test identified signatures of positive selection at the N-terminal ligand/receptor recognition domain of human CXCR1.

Bayesian signal processing

The application of Bayes' Theorem to signal processing provides a consistent framework for proceeding from prior knowledge to a posterior inference conditioned on both the prior knowledge and the observed signal data. The first part of the lecture will illustrate how the Bayesian methodology can be applied to a variety of signal processing problems. The second part of the lecture will introduce the concept of Markov Chain Monte-Carlo (MCMC) methods which is an effective approach to overcoming many of the analytical and computational problems inherent in statistical inference. Such techniques are at the centre of the rapidly developing area of Bayesian signal processing which, with the continual increase in available computational power, is likely to provide the underlying framework for most signal processing applications.

TOPS (Task optimization in the presence of signal-dependent noise) model

This paper proposes a movement trajectory planning model, which is a maximum task achievement model in which signal-dependent noise is added to the movement command. In the proposed model, two optimization criteria are combined, maximum task achievement and minimum energy consumption. The proposed model has the feature that the end-point boundary conditions for position, velocity, and acceleration need not be prespecified. Consequently, the method can be applied not only to the simple point-to-point movement, but to any task. In the method in this paper, the hand trajectory is derived by a psychophysical experiment and a numerical experiment for the case in which the target is not stationary, but is a moving region. It is shown that the trajectory predicted from the minimum jerk model or the minimum torque change model differs considerably from the results of the psychophysical experiment. But the trajectory predicted from the maximum task achievement model shows good qualitative agreement with the hand trajectory obtained from the psychophysical experiment. © 2004 Wiley Periodicals, Inc.

Microbial carbonate precipitation: Correlation of S-wave velocity with calcite precipitation

The use of microbial induced precipitation as a soil improvement technique has been growing in geotechnical domains where ureolytic bacteria that raise the pH of the system and induce calcium carbonate (CaCO3) precipitation are used. For many applications, it is useful to assess the degree of CaCO 3 precipitation by non-destructive testing. This study investigates the feasibility of S-wave velocity measurements to evaluate the amount of calcite precipitation by laboratory testing. Two sets of cemented specimen were tested. The first were samples terminated at different stages of cementation. The second were samples that went through different chemical treatments. These variations were made to find out if these factors would affect the S-wave velocity- cementation relationship. If chemical reaction efficiency was assumed to be constant throughout each test, the relationship between S-wave velocity (Vs) and the amount of CaCO3 precipitation was found to be approximately linear. This correlation between S-wave velocity and calcium carbonate precipitation validates its use as an indicator of the amount of calcite precipitation © 2011 ASCE.

Structured precision modelling with Cholesky basis superposition for speech recognition

Structured precision modelling is an important approach to improve the intra-frame correlation modelling of the standard HMM, where Gaussian mixture model with diagonal covariance are used. Previous work has all been focused on direct structured representation of the precision matrices. In this paper, a new framework is proposed, where the structure of the Cholesky square root of the precision matrix is investigated, referred to as Cholesky Basis Superposition (CBS). Each Cholesky matrix associated with a particular Gaussian distribution is represented as a linear combination of a set of Gaussian independent basis upper-triangular matrices. Efficient optimization methods are derived for both combination weights and basis matrices. Experiments on a Chinese dictation task showed that the proposed approach can significantly outperformed the direct structured precision modelling with similar number of parameters as well as full covariance modelling. © 2011 IEEE.

Correlation of cell numbers with catalase activities of pure strains of bacteria

An attempt was made to correlate the catalase production with the actual number of aerobic bacterial cells generating the enzyme: bacteria were obtained from the surface of marine fish. A linear correlation was found between the log of catalase activity and log of bacterial count in single culture.