Robust face recognition using posterior union model based neural networks

Face recognition with unknown, partial distortion and occlusion is a practical problem, and has a wide range of applications, including security and multimedia information retrieval. The authors present a new approach to face recognition subject to unknown, partial distortion and occlusion. The new approach is based on a probabilistic decision-based neural network, enhanced by a statistical method called the posterior union model (PUM). PUM is an approach for ignoring severely mismatched local features and focusing the recognition mainly on the reliable local features. It thereby improves the robustness while assuming no prior information about the corruption. We call the new approach the posterior union decision-based neural network (PUDBNN). The new PUDBNN model has been evaluated on three face image databases (XM2VTS, AT&T and AR) using testing images subjected to various types of simulated and realistic partial distortion and occlusion. The new system has been compared to other approaches and has demonstrated improved performance.

Particle Image Velocimetry Investigation of a finite amplitude pressure wave

Particle image velocimetry is used to study the motion of gas within a duct subject to the passage of a finite amplitude pressure wave. The wave is representative of the pressure waves found in the exhaust systems of internal combustion engines. Gas particles are accelerated from stationary to 150 m/s and then back to stationary in 8 ms. It is demonstrated that gas particles at the head of the wave travel at the same velocity across the duct cross section at a given point in time. Towards the tail of the wave viscous effects are plainly evident causing the flow profile to tend towards parabolic. However, the instantaneous mean particle velocity across the section is shown to match well with the velocity calculated from a corresponding measured pressure history using 1D gas dynamic theory. The measured pressure history at a point in the duct was acquired using a high speed pressure transducer of the type typically used for engine research in intake and exhaust systems. It is demonstrated that these are unable to follow the rapid changes in pressure accurately and that they are prone to resonate under certain circumstances.

Hidden Gems: systematically searching electronic databases for research publications for social work and social care.

Context: Electronic bibliographic databases are a key source for professional publications about social work and community care more generally. This article describes and evaluates a method of identifying relevant articles as part of a systematic review of research evidence. Decision making about institutional and home care services for older people is used as an example. Method: Four databases (Social Science Citation Index, Medline, CINAHL, and Caredata) that abstract publications relevant to health and social services were searched systematically to identify relevant research studies. The items retrieved were appraised independently using a standard form developed for the purpose. The searches were compared in terms of sensitivity, precision, overlap between databases, and inter-rater reliability. Results: The search retrieved 525 articles, of which 276 were relevant. The four databases retrieved 55%, 41%, 19%, and 1% of the relevant articles respectively, achieving these sensitivities with precision levels of 54%, 48%, 84% and 94%. The databases retrieved 116, 73, 24 and 15 unique relevant articles respectively, showing the need to use a range of databases. Discussion: A general approach to creating a search to retrieve relevant research has been developed. The development of an international, indexed database dedicated to literature relevant to social services is a priority to enable progress in evidence-based policy and practice in social work. Editors and researchers should consider using structured abstracts in order to improve the retrieval and dissemination of research.

Emotional speech: towards a new generation of databases

Research on speech and emotion is moving from a period of exploratory research into one where there is a prospect of substantial applications, notably in human-computer interaction. Progress in the area relies heavily on the development of appropriate databases. This paper addresses the issues that need to be considered in developing databases of emotional speech, and shows how the challenge of developing apropriate databases is being addressed in three major recent projects - the Belfast project, the Reading-Leeds project and the CREST-ESP project. From these and other studies the paper draws together the tools and methods that have been developed, addresses the problems that arise and indicates the future directions for the development of emotional speech databases.