Trust realisation in multi-domain collaborative environments

In the Internet-age, the geographical boundaries that have previously impinged upon inter-organisational collaborations have become decreasingly important. Of more importance for such collaborations is the notion and subsequent nature of trust - this is especially so in Grid-like environments where resources are both made available and subsequently accessed and used by remote users from a multitude of institutions with a variety of different privileges spanning across the collaborating resources. In this context, the ability to dynamically negotiate and subsequently enforce security policies driven by various levels of inter-organisational trust is essential. In this paper we present a dynamic trust negotiation (DTN) model and associated prototype implementation showing the benefits and limitations DTN incurs in supporting n-tier delegation hops needed for trust realisation in multi-domain collaborative environments

A critical analysis and validation of the accuracy of wave overtopping prediction formulae for OWECs

The development of wave energy devices is growing in recent years. One type of device is the overtopping wave energy converter (OWEC), for which the knowledge of the wave overtopping rates is a basic and crucial aspect in their design. In particular, the most interesting range to study is for OWECs with steep slopes to vertical walls, and with very small freeboards and zero freeboards where the overtopping rate is maximized, and which can be generalized as steep low-crested structures. Recently, wave overtopping prediction formulae have been published for this type of structures, although their accuracy has not been fully assessed, as the overtopping data available in this range is scarce. We performed a critical analysis of the overtopping prediction formulae for steep low-crested structures and the validation of the accuracy of these formulae, based on new overtopping data for steep low-crested structures obtained at Ghent University. This paper summarizes the existing knowledge about average wave overtopping, describes the physical model tests performed, analyses the results and compares them to existing prediction formulae. The new dataset extends the wave overtopping data towards vertical walls and zero freeboard structures. In general, the new dataset validated the more recent overtopping formulae focused on steep slopes with small freeboards, although the formulae are underpredicting the average overtopping rates for very small and zero relative crest freeboards

Accreditation of practice educators: An expectation too far ?

The successful completion of practice placements is essential to the education of occupational therapists; however, ensuring quality placements is challenging for occupational therapy educators. In 2000, Brunel University introduced a revised system of accreditation of practice educators which involved attendance at a course, the supervision of a student and the submission of an essay to be assessed. An audit revealed that a total of 314 therapists attended 15 courses between 2000 and 2003; of these, 243 (77%) subsequently supervised students and 32 (10%) became accredited. The requirement to accredit practice educators, which is a commendable attempt to ensure quality, may paradoxically have been detrimental in achieving quality. The College of Occupational Therapists’ apparent change of emphasis on this topic is welcome

Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Tracking

With efficient appearance learning models, Discriminative Correlation Filter (DCF) has been proven to be very successful in recent video object tracking benchmarks and competitions. However, the existing DCF paradigm suffers from two major issues, i.e., spatial boundary effect and temporal filter degradation. To mitigate these challenges, we propose a new DCF-based tracking method. The key innovations of the proposed method include adaptive spatial feature selection and temporal consistent constraints, with which the new tracker enables joint spatial-temporal filter learning in a lower dimensional discriminative manifold. More specifically, we apply structured spatial sparsity constraints to multi-channel filers. Consequently, the process of learning spatial filters can be approximated by the lasso regularisation. To encourage temporal consistency, the filter model is restricted to lie around its historical value and updated locally to preserve the global structure in the manifold. Last, a unified optimisation framework is proposed to jointly select temporal consistency preserving spatial features and learn discriminative filters with the augmented Lagrangian method. Qualitative and quantitative evaluations have been conducted on a number of well-known benchmarking datasets such as OTB2013, OTB50, OTB100, Temple-Colour, UAV123 and VOT2018. The experimental results demonstrate the superiority of the proposed method over the state-of-the-art approaches