The effects of different forms of advice on the control of a simulated complex system

Three experiments examine the effect of different forms of computer-generated advice on concurrent and subsequent performance of individuals controlling a simulated intensive-care task. Experiment 1 investigates the effect of optional and compulsory advice and shows that both result in an improvement in subjects' performance while receiving the advice, and also in an improvement in subsequent unaided performance. However, although the advice compliance displayed by the optional advice group shows a strong correlation with subsequent unaided performance, compulsory advice has no extra benefit over the optional use of advice. Experiment 2 examines the effect of providing users with on-line explanations of the advice, as well as providing less specific advice. The results show that both groups perform at the same level on the task as the advice groups from Experiment 1, although subjects receiving explanations scored significantly higher on a written post-task questionnaire. Experiment 3 investigates in more detail the relationship between advice compliance and performance. The results reveal a complex relationship between natural ability on the task and the following of advice, in that people who use the advice more tend to perform either better or worse than the more moderate users. The theoretical and practical implications of these experiments are discussed.

Teachers as researchers and teachers as software developers: how use-case analysis helps build better educational software

A series of government initiatives has raised both the profile of ICT in the curriculum and the expectation that high quality teaching and learning resources will be accessible across electronic networks. In order for e-learning resources such as websites to have the maximum educational impact, teachers need to be involved in their design and development. Use-case analysis provides a means of defining user requirements and other constraints in such a way that software developers can produce e-learning resources which reflect teachers' professional knowledge and support their classroom practice. It has some features in common with the participatory action research used to develop other aspects of classroom practice. Two case-studies are presented: one involves the development of an on-line resource centred on transcripts of original historical documents; the other describes how 'Learning how to Learn', a major, distributed research project funded under the ESRC Teaching and Learning Research Programme is using use-case analysis to develop web resources and services.

A study of the effects of adjunct cultures on the aroma compounds of Feta-type cheese

The influence of adjunct brine cultures on the volatile compounds in Feta-type cheeses made from bovine milk was studied. Four batches of brine were produced: one with no added adjuncts, a second containing Lactobacillus paracasei subsp. paracasei, a third containing Lb. paracasei subsp. paracasei plus Debaryomyces hansenii and a fourth with Lb. paracasei subsp. paracasei plus Yarrowia lipolytica. All the cultures were isolated from commercial Feta brines. Aroma compounds were analysed by dynamic headspace analysis, on-line coupled with GC/MS. The most important volatile compounds were quantified in the experimental cheeses; it was concluded that the use of Lb. paracasei subsp. paracasei and D. hansenii as adjuncts in the manufacture of Feta-type cheeses contribute to the formation of a richer pattern of aroma compounds, namely alcohols, aldehydes and esters. The inclusion of Y. lipolytica resulted in the production of undesirable aroma compounds that are not part of the usual volatile profile of high quality Feta cheeses. (C) 2004 Elsevier Ltd. All rights reserved.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Models for evolving networks: with applications in telecommunication and online activities

Driven by a range of modern applications that includes telecommunications, e-business and on-line social interaction, recent ideas in complex networks can be extended to the case of time-varying connectivity. Here we propose a general frame- work for modelling and simulating such dynamic networks, and we explain how the long time behaviour may reveal important information about the mechanisms underlying the evolution.

Shaking hands: Priming by social action effects

In a semi-naturalistic response-effect compatibility paradigm, participants were given the opportunity to learn that hand-shaking actions would be followed by social effects (human hand-shaking stimuli from a third-person perspective) or inanimate effects (block arrow stimuli). Relative to the actions, these effects appeared on the same or the opposite side of the screen (positional compatibility), and pointed towards or away from the response hand (directional compatibility). After learning, response times indicated a positional compatibility effect for both social and inanimate effects, but a directional compatibility effect occurred only for social action effects. These findings indicate that actions can be represented, not only by their effects on the inanimate world, but also by their effects on the actions of others. They are consistent with ideomotor theory, and with the view that actions are represented by bidirectional response-effect associations. They also have implications with respect to the origins and on-line control of imitation and the systems supporting imitation.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

On approximate electromagnetic cloaking by transformation media

We give a comprehensive study on regularized approximate electromagnetic cloaking in the spherical geometry via the transformation optics approach. The following aspects are investigated: (i) near-invisibility cloaking of passive media as well as active/radiating sources; (ii) the existence of cloak-busting inclusions without lossy medium lining; (iii) overcoming the cloaking-busts by employing a lossy layer outside the cloaked region; and (iv) the frequency dependence of the cloaking performances. We address these issues and connect the obtained asymptotic results to singular ideal cloaking. Numerical verifications and demonstrations are provided to show the sharpness of our analytical study.

Addressing animal health knowledge gaps in Southern Countries: the creation of a 2D animal health resource room

Livestock are a key asset for the global poor. However, access to relevant information is a critical issue for both livestock development practitioners and the poor themselves. Therefore, the following paper details the creation of an on-line Animal Health Resource Room. The aim was to create an immersive environment, which mimics the benefits of a 3D Virtual Learning Environment without the constraints on download times. Therefore, in the following paper key issues in the dissemination of such a platform such as connectivity and speed are explored within the wider context of the development of the tool itself.

Bistability through triadic closure

We propose and analyse a class of evolving network models suitable for describing a dynamic topological structure. Applications include telecommunication, on-line social behaviour and information processing in neuroscience. We model the evolving network as a discrete time Markov chain, and study a very general framework where, conditioned on the current state, edges appear or disappear independently at the next timestep. We show how to exploit symmetries in the microscopic, localized rules in order to obtain conjugate classes of random graphs that simplify analysis and calibration of a model. Further, we develop a mean field theory for describing network evolution. For a simple but realistic scenario incorporating the triadic closure effect that has been empirically observed by social scientists (friends of friends tend to become friends), the mean field theory predicts bistable dynamics, and computational results confirm this prediction. We also discuss the calibration issue for a set of real cell phone data, and find support for a stratified model, where individuals are assigned to one of two distinct groups having different within-group and across-group dynamics.

The effects of word exposure frequency and elaboration of word processing on incidental L2 vocabulary acquisition through reading

Research on incidental second language (L2) vocabulary acquisition through reading has claimed that repeated encounters with unfamiliar words and the relative elaboration of processing these words facilitate word learning. However, so far both variables have been investigated in isolation. To help close this research gap, the current study investigates the differential effects of the variables ‘word exposure frequency’ and ‘elaboration of word processing’ on the initial word learning and subsequent word retention of advanced learners of L2 English. Whereas results showed equal effects for both variables on initial word learning, subsequent word retention was more contingent on elaborate processing of form–meaning relationships than on word frequency. These results, together with those of the studies reviewed, suggest that processing words again after reading (input–output cycles) is superior to reading-only tasks. The findings have significant implications for adaptation and development of teaching materials that enhance L2 vocabulary learning.

Acoustic scattering by an inhomogeneous layer on a rigid plate

The problem of scattering of time-harmonic acoustic waves by an inhomogeneous fluid layer on a rigid plate in R2 is considered. The density is assumed to be unity in the media: within the layer the sound speed is assumed to be an arbitrary bounded measurable function. The problem is modelled by the reduced wave equation with variable wavenumber in the layer and a Neumann condition on the plate. To formulate the problem and prove uniqueness of solution a radiation condition appropriate for scattering by infinite rough surfaces is introduced, a generalization of the Rayleigh expansion condition for diffraction gratings. With the help of the radiation condition the problem is reformulated as a system of two second kind integral equations over the layer and the plate. Under additional assumptions on the wavenumber in the layer, uniqueness of solution is proved and the nonexistence of guided wave solutions of the homogeneous problem established. General results on the solvability of systems of integral equations on unbounded domains are used to establish existence and continuous dependence in a weighted norm of the solution on the given data.