Experimentally validated continuous-time repetitive control of non-minimum phase plants with a prescribed degree of stability

This paper considers the application of continuous-time repetitive control to non-minimum phase plants in a continuous-time model predictive control setting. In particular, it is shown how some critical performance problems associated with repetitive control of such plants can be avoided by use of predictive control with a prescribed degree of stability. The results developed are first illustrated by simulation studies and then through experimental tests on a non-minimum phase electro-mechanical system

Real-time human action recognition on an embedded, reconfigurable video processing architecture

Copyright @ 2008 Springer-Verlag.In recent years, automatic human motion recognition has been widely researched within the computer vision and image processing communities. Here we propose a real-time embedded vision solution for human motion recognition implemented on a ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human motion recognition system with simple motion features and a linear Support Vector Machine (SVM) classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template (eg. “motion history image”) class of approaches. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfiured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemented a human motion recognition system on this reconfigurable architecture. With a small number of human actions (hand gestures), this stand-alone system is performing reliably, with an 80% average recognition rate using limited training data. This type of system has applications in security systems, man-machine communications and intelligent environments.DTI and Broadcom Ltd

A decision support system for drinking water production integrating health risks assessment

The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation

Participant Feedback in the Evaluation of Novel Stroke Rehabilitation Technologies

Purpose: Stroke participant perspectives are used to evaluate a novel rehabilitation system employing electrical stimulation (ES) technology combined with robotic assistance and virtual reality. The broader implications of such feedback for future technological development are discussed. Method: While supported by a robot, ES was applied to the triceps and anterior deltoid muscles of 5 chronic stroke participants with upper limb impairment to assist them in completing functional, virtual reality tracking tasks. Advanced ES controllers adjusted the amount of ES applied on each attempt to improve accuracy and maximise voluntary effort. The system was evaluated in terms of participants’ perspectives, expressed during a semi-structured interview, and clinical outcome measures. Results: The rehabilitation system was well accepted by participants and viewed positively, despite mixed opinions regarding effectiveness. Feedback demonstrated an alignment in participants’ perceptions of reduced impairment and clinical outcomes, in which a significant (p < 0.001) mean change of 9.3 in Fugl-Meyer scores was observed. Participant feedback also provided insight into individual differences observed in clinical outcomes. From our findings six key issues regarding effectiveness, muscles trained, system flexibility and portability, possible discomfort and the value of participant perspectives emerged that may be relevant for researchers developing new rehabilitation technologies. Conclusion: Participant feedback via a semi-structured interview provided important insight into the usability and effectiveness of using this system as a platform for upper limb stroke rehabilitation

Newsprint coverage of smoking in cars carrying children : a case study of public and scientific opinion driving the policy debate

Acknowledgements Date of Acceptance:17/10/2014 Acknowledgements: This project was funded by Cancer Research UK (MC_U130085862) and the Scottish School of Public Health Research. Cancer Research UK and the Scottish School of Public Health Research was not involved in the collection, analysis, and interpretation of data, writing of the manuscript or the decision to submit the manuscript for publication. Shona Hilton, Karen Wood, Josh Bain and Chris Patterson are funded by the UK Medical Research Council as part of the Understandings and Uses of Public Health Research programme (MC_UU_12017/6) at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow. We thank Alan Pollock who provided assistance with coding.Peer reviewedPublisher PD

Critical animal and media studies: Expanding the understanding of oppression in communication research

Critical and communication studies have traditionally neglected the oppression conducted by humans towards other animals. However, our (mis)treatment of other animals is the result of public consent supported by a morally speciesist-anthropocentric system of values. Speciesism or anthroparchy, as much as any other mainstream ideologies, feeds the media and at the same time is perpetuated by them. The goal of this article is to remedy this neglect by introducing the subdiscipline of Critical Animal and Media Studies. Critical Animal and Media Studies takes inspiration both from critical animal studies – which is so far the most consolidated critical field of research in the social sciences addressing our exploitation of other animals – and from the normative-moral stance rooted in the cornerstones of traditional critical media studies. The authors argue that the Critical Animal and Media Studies approach is an unavoidable step forward for critical media and communication studies to engage with the expanded circle of concerns of contemporary ethical thinking

The XMM Cluster Survey: X-ray analysis methodology

The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we describe the data processing methodology applied to the 5,776 XMM observations used to construct the current XCS source catalogue. A total of 3,675 > 4-sigma cluster candidates with > 50 background-subtracted X-ray counts are extracted from a total non-overlapping area suitable for cluster searching of 410 deg^2. Of these, 993 candidates are detected with > 300 background-subtracted X-ray photon counts, and we demonstrate that robust temperature measurements can be obtained down to this count limit. We describe in detail the automated pipelines used to perform the spectral and surface brightness fitting for these candidates, as well as to estimate redshifts from the X-ray data alone. A total of 587 (122) X-ray temperatures to a typical accuracy of < 40 (< 10) per cent have been measured to date. We also present the methodology adopted for determining the selection function of the survey, and show that the extended source detection algorithm is robust to a range of cluster morphologies by inserting mock clusters derived from hydrodynamical simulations into real XMM images. These tests show that the simple isothermal beta-profiles is sufficient to capture the essential details of the cluster population detected in the archival XMM observations. The redshift follow-up of the XCS cluster sample is presented in a companion paper, together with a first data release of 503 optically-confirmed clusters.Comment: MNRAS accepted, 45 pages, 38 figures. Our companion paper describing our optical analysis methodology and presenting a first set of confirmed clusters has now been submitted to MNRA