Status and applicability of solid polymer electrolyte technology to electrolytic hydrogen and oxygen production

The solid polymer electrolyte (SPE) water electrolysis technology is presented as a potential energy conversion method for wind driven generator systems. Electrolysis life and performance data are presented from laboratory sized single cells (7.2 sq in active area) with high cell current density selected (1000 ASF) for normal operation

Loopy belief propagation and probabilistic image processing

Estimation of hyperparameters by maximization of the marginal likelihood in probabilistic image processing is investigated by using the cluster variation method. The algorithms are substantially equivalent to generalized loopy belief propagation

Do unbalanced data have a negative effect on LDA?

For two-class discrimination, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] claimed that, when covariance matrices of the two classes were unequal, a (class) unbalanced data set had a negative effect on the performance of linear discriminant analysis (LDA). Through re-balancing 10 real-world data sets, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] provided empirical evidence to support the claim using AUC (Area Under the receiver operating characteristic Curve) as the performance metric. We suggest that such a claim is vague if not misleading, there is no solid theoretical analysis presented in Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562], and AUC can lead to a quite different conclusion from that led to by misclassification error rate (ER) on the discrimination performance of LDA for unbalanced data sets. Our empirical and simulation studies suggest that, for LDA, the increase of the median of AUC (and thus the improvement of performance of LDA) from re-balancing is relatively small, while, in contrast, the increase of the median of ER (and thus the decline in performance of LDA) from re-balancing is relatively large. Therefore, from our study, there is no reliable empirical evidence to support the claim that a (class) unbalanced data set has a negative effect on the performance of LDA. In addition, re-balancing affects the performance of LDA for data sets with either equal or unequal covariance matrices, indicating that having unequal covariance matrices is not a key reason for the difference in performance between original and re-balanced data

Short note on two output-dependent hidden Markov models

The purpose of this note is to study the assumption of mutual information independence", which is used by Zhou (2005) for deriving an output-dependent hidden Markov model, the so-called discriminative HMM (D-HMM), in the context of determining a stochastic optimal sequence of hidden states. The assumption is extended to derive its generative counterpart, the G-HMM. In addition, state-dependent representations for two output-dependent HMMs, namely HMMSDO (Li, 2005) and D-HMM, are presented

Variational bayes for estimating the parameters of a hidden Potts model

Hidden Markov random field models provide an appealing representation of images and other spatial problems. The drawback is that inference is not straightforward for these models as the normalisation constant for the likelihood is generally intractable except for very small observation sets. Variational methods are an emerging tool for Bayesian inference and they have already been successfully applied in other contexts. Focusing on the particular case of a hidden Potts model with Gaussian noise, we show how variational Bayesian methods can be applied to hidden Markov random field inference. To tackle the obstacle of the intractable normalising constant for the likelihood, we explore alternative estimation approaches for incorporation into the variational Bayes algorithm. We consider a pseudo-likelihood approach as well as the more recent reduced dependence approximation of the normalisation constant. To illustrate the effectiveness of these approaches we present empirical results from the analysis of simulated datasets. We also analyse a real dataset and compare results with those of previous analyses as well as those obtained from the recently developed auxiliary variable MCMC method and the recursive MCMC method. Our results show that the variational Bayesian analyses can be carried out much faster than the MCMC analyses and produce good estimates of model parameters. We also found that the reduced dependence approximation of the normalisation constant outperformed the pseudo-likelihood approximation in our analysis of real and synthetic datasets

Kernel Ellipsoidal Trimming

Ellipsoid estimation is an issue of primary importance in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and novelty/outlier detection. This paper presents a new method of kernel information matrix ellipsoid estimation (KIMEE) that finds an ellipsoid in a kernel defined feature space based on a centered information matrix. Although the method is very general and can be applied to many of the aforementioned problems, the main focus in this paper is the problem of novelty or outlier detection associated with fault detection. A simple iterative algorithm based on Titterington's minimum volume ellipsoid method is proposed for practical implementation. The KIMEE method demonstrates very good performance on a set of real-life and simulated datasets compared with support vector machine methods

Body Theology

Body Theology investigates the human body as a place where landscape, myth and bacteria intersect to create numerous imaginary realms. Horizon lines shift or disappear completely, and the overall dark palette sets a tone intended to evoke mystery. In these paintings, it may be difficult to determine whether inside is outside, up is down, big is small, or figure is ground. I embrace this ambiguity and invite the viewer to participate in a visual and metaphorical adventure. My painting process is traditional: from a white ground, many layers of semi-transparent oil paint begin with loose and rhythmic brush strokes. I enjoy how the nature of the paint itself reflects the fluidity and luminosity found in both inner and outer worlds. I never know exactly what the finished image will look like when I begin. Unforeseen problems require creative solutions, new forms and ideas emerge from the destruction of old ones, and my own understanding of the picture evolves through formal development and intuition

Challenges for the Northern Ireland tourist board in marketing Northern Ireland

Northern Ireland (NI) is located on the northeast quadrant of the Irish land mass, and encompasses the six counties. While NI may be physically located on the island of Ireland, it is not a part of the Republic of Ireland. Rather, it is a part of the United Kingdom. The Republic of Ireland (more commonly referred to by Northern Irelanders as just the "South") gained independence from the United Kingdom in 1921. The predominance of those citizens loyal to Great Britain were located in the North. So, rather than risk major conflicts, the British government decided to maintain rule over six of the nine counties of the north of Ireland and called this area "Northern Ireland". Even the border between the north and south is controversial, in some areas, one farm is in the South (or the Republic of Ireland), while directly across the road, a brother's farm is located in the North. In fact, the northern most point on the island of Ireland is not in NI, but rather in the South. So, one can see how confusing it can be for both the local and the tourist alike. The political aspects of Northern Ireland can also be very confusing. The republicans feel that it should be a part of the Republic of Ireland. The unionists and loyalists feel that it should remain a part of the United Kingdom. There are many different loyalist and republican groups, each with different messages.peer-reviewe