Learning in neural networks and stochastic approximation methods with averaging

The problem of adjusting the weights (learning) in multilayer feedforward neural networks (NN) is known to be of a high importance when utilizing NN techniques in various practical applications. The learning procedure is to be performed as fast as possible and in a simple computational fashion, the two requirements which are usually not satisfied practically by the methods developed so far. Moreover, the presence of random inaccuracies are usually not taken into account. In view of these three issues, an alternative stochastic approximation approach discussed in the paper, seems to be very promising.

Determination of the degradation kinetics of anthocyanins in a model juice system using isothermal and non-isothermal methods

The effect of temperature on the degradation of blackcurrant anthocyanins in a model juice system was determined over a temperature range of 4–140 °C. The thermal degradation of anthocyanins followed pseudo first-order kinetics. From 4–100 °C an isothermal method was used to determine the kinetic parameters. In order to mimic the temperature profile in retort systems, a non-isothermal method was applied to determine the kinetic parameters in the model juice over the temperature range 110–140 °C. The results from both isothermal and non-isothermal methods fit well together, indicating that the non-isothermal procedure is a reliable mathematical method to determine the kinetics of anthocyanin degradation. The reaction rate constant (k) increased from 0.16 (±0.01) × 10−3 to 9.954 (±0.004) h−1 at 4 and 140 °C, respectively. The temperature dependence of the rate of anthocyanin degradation was modelled by an extension of the Arrhenius equation, which showed a linear increase in the activation energy with temperature.

Livestock and learning: evaluation of a prototype 3D virtual learning environment for livestock practitioners in India and Bolivia

Livestock are a key asset for the global poor. However, access to relevant information is a critical issue for both the poor and the practitioners who serve them. Therefore, the authors describe a web-based Virtual Learning Environment to disseminate educational materials on priority animal health constraints in Bolivia and India. The aim was to explore demand for 3D among development practitioners in the South. Two wider arguments from the ICT4D literature framed the analysis: the concept of 3D as a ‘lead technology’ and the relevance of Internet skills to the adoption of a 3D format. The results illustrated that neither construct influenced demand. Rather, study participants were ready adopters but desired greater levels of interaction and thereby, a more collaborative learning environment. Therefore, 3D has a number of potential benefits to enhance knowledge sharing among community practitioners in the Global South.

Classification and fault detection methods for fuel cell monitoring and quality control

In this paper, various types of fault detection methods for fuel cells are compared. For example, those that use a model based approach or a data driven approach or a combination of the two. The potential advantages and drawbacks of each method are discussed and comparisons between methods are made. In particular, classification algorithms are investigated, which separate a data set into classes or clusters based on some prior knowledge or measure of similarity. In particular, the application of classification methods to vectors of reconstructed currents by magnetic tomography or to vectors of magnetic field measurements directly is explored. Bases are simulated using the finite integration technique (FIT) and regularization techniques are employed to overcome ill-posedness. Fisher's linear discriminant is used to illustrate these concepts. Numerical experiments show that the ill-posedness of the magnetic tomography problem is a part of the classification problem on magnetic field measurements as well. This is independent of the particular working mode of the cell but influenced by the type of faulty behavior that is studied. The numerical results demonstrate the ill-posedness by the exponential decay behavior of the singular values for three examples of fault classes.

On SETAR non-linearity and forecasting

We compare linear autoregressive (AR) models and self-exciting threshold autoregressive (SETAR) models in terms of their point forecast performance, and their ability to characterize the uncertainty surrounding those forecasts, i.e. interval or density forecasts. A two-regime SETAR process is used as the data-generating process in an extensive set of Monte Carlo simulations, and we consider the discriminatory power of recently developed methods of forecast evaluation for different degrees of non-linearity. We find that the interval and density evaluation methods are unlikely to show the linear model to be deficient on samples of the size typical for macroeconomic data

Gender and the evaluation of research

This study examines if and how gender relates to research evaluation via panel assessment and journal ratings lists. Using data from UK business schools we find no evidence that the proportion of women in a submission for panel assessment affected the score received by the submitting institution. However, we do find that women on average receive lower scores according to some journal ratings lists. There are important differences in the rated quality of journals that men and women publish in across the sub-disciplines with men publishing significantly more research in the highest rated accountancy, information management and strategy journals. In addition, women who are able to utilise networks to co-author with individuals outside their institution are able to publish in higher-rated journals, although the same is not true for men; women who are attributed with “individual staff circumstances” (e.g. maternity leave or part-time working) have lower scores according to journal ratings lists.

Acoustic scattering : high frequency boundary element methods and unified transform methods

We describe some recent advances in the numerical solution of acoustic scattering problems. A major focus of the paper is the efficient solution of high frequency scattering problems via hybrid numerical-asymptotic boundary element methods. We also make connections to the unified transform method due to A. S. Fokas and co-authors, analysing particular instances of this method, proposed by J. A. De-Santo and co-authors, for problems of acoustic scattering by diffraction gratings.

Sensory and consumer science methods used with older adults: a review of current methods and recommendations for the future

Capturing the sensory perception and preferences of older adults, whether healthy or with particular disease states, poses major methodological challenges for the sensory community. Currently a vastly under researched area, it is at the same time a vital area of research as alterations in sensory perception can affect daily dietary food choices, intake, health and wellbeing. Tailored sensory methods are needed that take into account the challenges of working with such populations including poor access leading to low patient numbers (study power), cognitive abilities, use of medications, clinical treatments and context (hospitals and care homes). The objective of this paper was to review current analytical and affective sensory methodologies used with different cohorts of healthy and frail older adults, with focus on food preference and liking. We particularly drew attention to studies concerning general ageing as well as to those considering age-related diseases that have an emphasis on malnutrition and weight loss. Pubmed and Web of Science databases were searched to 2014 for relevant articles in English. From this search 75 papers concerning sensory acuity, 41 regarding perceived intensity and 73 relating to hedonic measures were reviewed. Simpler testing methods, such as directional forced choice tests and paired preference tests need to be further explored to determine whether they lead to more reliable results and better inter-cohort comparisons. Finally, sensory quality and related quality of life for older adults suffering from dementia must be included and not ignored in our future actions.

Decadal predictions with the HiGEM high resolution global coupled climate model: description and basic evaluation

This paper describes the development and basic evaluation of decadal predictions produced using the HiGEM coupled climate model. HiGEM is a higher resolution version of the HadGEM1 Met Office Unified Model. The horizontal resolution in HiGEM has been increased to 1.25◦ × 0.83◦ in longitude and latitude for the atmosphere, and 1/3◦ × 1/3◦ globally for the ocean. The HiGEM decadal predictions are initialised using an anomaly assimilation scheme that relaxes anomalies of ocean temperature and salinity to observed anomalies. 10 year hindcasts are produced for 10 start dates (1960, 1965,..., 2000, 2005). To determine the relative contributions to prediction skill from initial conditions and external forcing, the HiGEM decadal predictions are compared to uninitialised HiGEM transient experiments. The HiGEM decadal predictions have substantial skill for predictions of annual mean surface air temperature and 100 m upper ocean temperature. For lead times up to 10 years, anomaly correlations (ACC) over large areas of the North Atlantic Ocean, the Western Pacific Ocean and the Indian Ocean exceed values of 0.6. Initialisation of the HiGEM decadal predictions significantly increases skill over regions of the Atlantic Ocean,the Maritime Continent and regions of the subtropical North and South Pacific Ocean. In particular, HiGEM produces skillful predictions of the North Atlantic subpolar gyre for up to 4 years lead time (with ACC > 0.7), which are significantly larger than the uninitialised HiGEM transient experiments.