Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

A leadership framework to support the use of e-learning resources

Aim
This inquiry aims to apply the NHS leadership framework to nurse education for the implementation of e-learning.
Background
Recognition needs to be given to the emerging postgraduate nursing students new status of consumer and the challenge now for nurse education is how to remain relevant and competitive in this consumer led market. The move towards an e-learning paradigm has been suggested as a competitive and contemporary way forward for the student consumer. The successful introduction of e-learning in nurse education will require leadership and a strong organisational management system.
Discussion
Each element of the NHS leadership framework is described and interpreted for application in a higher education setting for the implementation of e-learning.
Conclusions
Change in the delivery of post graduate nurse education is necessary to ensure it remains current and reflective of consumer need in a competitive marketplace. By applying a leadership framework that acknowledges the skills and abilities of staff and encourages the formation of collaborative partnerships from within the wider university community, educators can begin to develop skills and confidence in teaching using e-learning resources.

The relationship between the recognition of facial expressions and self-reported anger in people with intellectual disabilities

Background This study aims to examine the relationship between how individuals with intellectual disabilities report their own levels of anger, and the ability of those individuals to recognize emotions. It was hypothesized that increased expression of anger would be linked to lower ability to recognize facial emotional expressions and increased tendency to interpret facial expressions in a hostile or negative manner. It was also hypothesized increased levels of anger may lead to the altered perception of a particular emotion.

Method A cross-sectional survey design was used. Thirty participants completed a test of facial emotion recognition (FER), and a self-report anger inventory (Benson & Ivins 1992) as part of a structured interview.

Results Individuals with higher self-reported anger did not show significantly reduced performance in FER, or interpret facial expressions in a more hostile manner compared with individuals with less self-reported anger. However, they were less accurate in recognizing neutral facial emotions.

Conclusions It is tentatively suggested that individuals with high levels of anger may be likely to perceive emotional content in a neutral facial expression because of their high levels of emotional arousal.

Valuing the cultural monuments of Armenia: Bayesian updating of prior beliefs in contingent valuation

The most appropriate way to measure the social benefits of conserving built cultural heritage sites is to ask the beneficiaries of conservation interventions how much they would be willing to pay for them. We use contingent valuation - a survey-based approach that elicits willingness to pay (WTP) directly from individuals - to estimate the benefits of a nationwide conservation of built cultural heritage sites in Armenia. The survey was administered to Armenian nationals living in Armenia, and obtained extensive information about the respondents' perceptions of the current state of conservation of monuments in Armenia, described the current situation, presented a hypothetical conservation program, elicited WTP for it, and queried individuals about what they thought would happen to monument sites in the absence of the government conservation program. We posit that respondents combined the information about the fate of monuments provided by the questionnaire with their prior beliefs, and that WTP for the good, or program, is likely to be affected by these updated beliefs. We propose a Bayesian updating model of prior beliefs, and empirically implement it with the data from our survey. We found that uncertainty about what would happen to monuments in the absence of the program results in lower WTP amounts. © 2008 Pion Ltd and its Licensors.