16 resultados para Training systems

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input-multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate some of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-plus-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. Finally, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with a sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.

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Aim The aim of the study is to evaluate factors that enable or constrain the implementation and service delivery of early warnings systems or acute care training in practice. Background To date there is limited evidence to support the effectiveness of acute care initiatives (early warning systems, acute care training, outreach) in reducing the number of adverse events (cardiac arrest, death, unanticipated Intensive Care admission) through increased recognition and management of deteriorating ward based patients in hospital [1-3]. The reasons posited are that previous research primarily focused on measuring patient outcomes following the implementation of an intervention or programme without considering the social factors (the organisation, the people, external influences) which may have affected the process of implementation and hence measured end-points. Further research which considers the social processes is required in order to understand why a programme works, or does not work, in particular circumstances [4]. Method The design is a multiple case study approach of four general wards in two acute hospitals where Early Warning Systems (EWS) and Acute Life-threatening Events Recognition and Treatment (ALERT) course have been implemented. Various methods are being used to collect data about individual capacities, interpersonal relationships and institutional balance and infrastructures in order to understand the intended and unintended process outcomes of implementing EWS and ALERT in practice. This information will be gathered from individual and focus group interviews with key participants (ALERT facilitators, nursing and medical ALERT instructors, ward managers, doctors, ward nurses and health care assistants from each hospital); non-participant observation of ward organisation and structure; audit of patients' EWS charts and audit of the medical notes of patients who deteriorated during the study period to ascertain whether ALERT principles were followed. Discussion & progress to date This study commenced in January 2007. Ethical approval has been granted and data collection is ongoing with interviews being conducted with key stakeholders. The findings from this study will provide evidence for policy-makers to make informed decisions regarding the direction for strategic and service planning of acute care services to improve the level of care provided to acutely ill patients in hospital. References 1. Esmonde L, McDonnell A, Ball C, Waskett C, Morgan R, Rashidain A et al. Investigating the effectiveness of Critical Care Outreach Services: A systematic review. Intensive Care Medicine 2006; 32: 1713-1721 2. McGaughey J, Alderdice F, Fowler R, Kapila A, Mayhew A, Moutray M. Outreach and Early Warning Systems for the prevention of Intensive Care admission and death of critically ill patients on general hospital wards. Cochrane Database of Systematic Reviews 2007, Issue 3. www.thecochranelibrary.com 3. Winters BD, Pham JC, Hunt EA, Guallar E, Berenholtz S, Pronovost PJ (2007) Rapid Response Systems: A systematic review. Critical Care Medicine 2007; 35 (5): 1238-43 4. Pawson R and Tilley N. Realistic Evaluation. London; Sage: 1997

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Statement of purpose The purpose of this concurrent session is to present the main findings and recommendations from a five year study evaluating the implementation of Early Warning Systems (EWS) and the Acute Life-threatening Events: Recognition and Treatment (ALERT) course in Northern Ireland. The presentation will provide delegates with an understanding of those factors that enable and constrain successful implementation of EWS and ALERT in practice in order to provide an impetus for change. Methods The research design was a multiple case study approach of four wards in two hospitals in Northern Ireland. It followed the principles of realist evaluation research which allowed empirical data to be gathered to test and refine RRS programme theory [1]. The stages included identifying the programme theories underpinning EWS and ALERT, generating hypotheses, gathering empirical evidence and refining the programme theories. This approach used a variety of mixed methods including individual and focus group interviews, observation and documentary analysis of EWS compliance data and ALERT training records. A within and across case comparison facilitated the development of mid-range theories from the research evidence. Results The official RRS theories developed from the realist synthesis were critically evaluated and compared with the study findings to develop a mid-range theory to explain what works, for whom in what circumstances. The findings of what works suggests that clinical experience, established working relationships, flexible implementation of protocols, ongoing experiential learning, empowerment and pre-emptive management are key to the success of EWS and ALERT implementation. Each concept is presented as ‘context, mechanism and outcome configurations’ to provide an understanding of how the context impacts on individual reasoning or behaviour to produce certain outcomes. Conclusion These findings highlight the combination of factors that can improve the implementation and sustainability of EWS and ALERT and in light of this evidence several recommendations are made to provide policymakers with guidance and direction for future policy development. References: 1. Pawson R and Tilley N. (1997) Realistic Evaluation. Sage Publications; London Type of submission: Concurrent session Source of funding: Sandra Ryan Fellowship funded by the School of Nursing & Midwifery, Queen’s University of Belfast

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Background: Developing complex interventions for testing in randomised controlled trials is of increasing importance in healthcare planning. There is a need for careful design of interventions for secondary prevention of coronary heart disease (CHD). It has been suggested that integrating qualitative research in the development of a complex intervention may contribute to optimising its design but there is limited evidence of this in practice. This study aims to examine the contribution of qualitative research in developing a complex intervention to improve the provision and uptake of secondary prevention of CHD within primary care in two different healthcare systems.

Methods: In four general practices, one rural and one urban, in Northern Ireland and the Republic of Ireland, patients with CHD were purposively selected. Four focus groups with patients (N = 23) and four with staff (N = 29) informed the development of the intervention by exploring how it could be tailored and integrated with current secondary prevention activities for CHD in the two healthcare settings. Following an exploratory trial the acceptability and feasibility of the intervention were discussed in four focus groups (17 patients) and 10 interviews (staff). The data were analysed using thematic analysis.

Results: Integrating qualitative research into the development of the intervention provided depth of information about the varying impact, between the two healthcare systems, of different funding and administrative arrangements, on their provision of secondary prevention and identified similar barriers of time constraints, training needs and poor patient motivation. The findings also highlighted the importance to patients of stress management, the need for which had been underestimated by the researchers. The qualitative evaluation provided depth of detail not found in evaluation questionnaires. It highlighted how the intervention needed to be more practical by minimising administration, integrating role plays into behaviour change training, providing more practical information about stress management and removing self-monitoring of lifestyle change.

Conclusion: Qualitative research is integral to developing the design detail of a complex intervention and tailoring its components to address individuals' needs in different healthcare systems. The findings highlight how qualitative research may be a valuable component of the preparation for complex interventions and their evaluation.

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A new algorithm for training of nonlinear optimal neuro-controllers (in the form of the model-free, action-dependent, adaptive critic paradigm). Overcomes problems with existing stochastic backpropagation training: need for data storage, parameter shadowing and poor convergence, offering significant benefits for online applications.

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Across the UK recent policy developments have focused on improved information sharing and inter-agency cooperation. Professional non-reporting of child maltreatment concerns has been consistently highlighted as a problem in a range of countries and the research literature indicates that this can happen for a variety of reasons. Characteristics such as the type of abuse and the threshold of evidence available are key factors, as are concerns that reporting will damage the professional-client relationship. Professional discipline can also impact on willingness to report, as can personal beliefs about abuse, attitudes towards child protection services and experiences of court processes. Research examining the role of organisational factors in information sharing and reporting emphasises the importance of training and there are some positive indications that training can increase professional awareness of reporting processes and requirements and help to increase knowledge of child abuse and its symptoms. Nonetheless, this is a complex issue and the need for training to go beyond simple awareness raising is recognised. In order to tackle non-reporting in a meaningful way, childcare professionals need access to on-going multidisciplinary training which is specifically tailored to address the range of different factors which impact on reporting attitudes and behaviours.

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There is an increased interest in higher education in the use of e-learning resources for students. This can be attributed to many factors including, the availability of advanced technology systems, a growing student population that is technology focused, financial implications and the recruitment of international students. However, the introduction of technology and e-learning into teaching has given rise to issues regarding quality and quantity of educational practice . The challenge now is for educationalists is to deliver an optimal learning experience that is effective and appropriate for students’ learning needs.

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This paper presents a novel method of audio-visual feature-level fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there are limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new multimodal feature representation and a modified cosine similarity are introduced to combine and compare bimodal features with limited training data, as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal dataset created from the SPIDRE speaker recognition database and AR face recognition database with variable noise corruption of speech and occlusion in the face images. The system's speaker identification performance on the SPIDRE database, and facial identification performance on the AR database, is comparable with the literature. Combining both modalities using the new method of multimodal fusion leads to significantly improved accuracy over the unimodal systems, even when both modalities have been corrupted. The new method also shows improved identification accuracy compared with the bimodal systems based on multicondition model training or missing-feature decoding alone.

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We consider the uplink of massive multicell multiple-input multiple-output systems, where the base stations (BSs), equipped with massive arrays, serve simultaneously several terminals in the same frequency band. We assume that the BS estimates the channel from uplink training, and then uses the maximum ratio combining technique to detect the signals transmitted from all terminals in its own cell. We propose an optimal resource allocation scheme which jointly selects the training duration, training signal power, and data signal power in order to maximize the sum spectral efficiency, for a given total energy budget spent in a coherence interval. Numerical results verify the benefits of the optimal resource allocation scheme. Furthermore, we show that more training signal power should be used at low signal-to-noise ratio (SNRs), and vice versa at high SNRs. Interestingly, for the entire SNR regime, the optimal training duration is equal to the number of terminals.

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Background Rapid Response Systems (RRS) consist of four interrelated and interdependent components; an event detection and trigger mechanism, a response strategy, a governance structure and process improvement system. These multiple components of the RRS pose problems in evaluation as the intervention is complex and cannot be evaluated using a traditional systematic review. Complex interventions in healthcare aimed at changing service delivery and related behaviour of health professionals require a different approach to summarising the evidence. Realist synthesis is such an approach to reviewing research evidence on complex interventions to provide an explanatory analysis of how and why an intervention works or doesn’t work in practice. The core principle is to make explicit the underlying assumptions about how an intervention is suppose to work (ie programme theory) and then use this theory to guide evaluation. Methods A realist synthesis process was used to explain those factors that enable or constrain the success of RRS programmes. Results The findings from the review include the articulation of the RRS programme theories, evaluation of whether these theories are supported or refuted by the research evidence and an evaluation of evidence to explain the underlying reasons why RRS works or doesn’t work in practice. Rival conjectured RRS programme theories were identified to explain the constraining factors regarding implementation of RRS in practice. These programme theories are presented using a logic model to highlight all the components which impact or influence the delivery of RRS programmes in the practice setting. The evidence from the realist synthesis provided the foundation for the development of hypothesis to test and refine the theories in the subsequent stages of the Realist Evaluation PhD study [1]. This information will be useful in providing evidence and direction for strategic and service planning of acute care to improve patient safety in hospital. References: McGaughey J, Blackwood B, O’Halloran P, Trinder T. J. & Porter S. (2010) Realistic Evaluation of Early Warning Systems and the Acute Life-threatening Events – Recognition and Treatment training course for early recognition and management of deteriorating ward-based patients: research protocol. Journal of Advanced Nursing 66 (4), 923-932.

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Symposium Chair: Dr Jennifer McGaughey

Title: Early Warning Systems: problems, pragmatics and potential

Early Warning Systems (EWS) provide a mechanism for staff to recognise, refer and manage deteriorating patients on general hospital wards. Implementation of EWS in practice has required considerable change in the delivery of critical care across hospitals. Drawing their experience of these changes the authors will demonstrate the problems and potential of using EWS to improve patient outcomes.

The first paper (Dr Jennifer McGaughey: Early Warning Systems: what works?) reviews the research evidence regarding the factors that support or constrain the implementation of Early Warning System (EWS) in practice. These findings explain those processes which impact on the successful achievement of patient outcomes. In order to improve detection and standardise practice National EWS have been implemented in the United Kingdom. The second paper (Catherine Plowright: The implementation of the National EWS in a District General Hospital) focuses on the process of implementing and auditing a National EWS. This process improvement is essential to contribute to future collaborative research and collection of robust datasets to improve patient safety as recommended by the Royal College of Physicians (RCP 2012). To successfully implement NEWS in practice requires strategic planning and staff education. The practical issues of training staff is discussed in the third paper. This paper (Collette Laws-Chapman: Simulation as a modality to embed the use of Early Warning Systems) focuses on using simulation and structured debrief to enhance learning in the early recognition and management of deteriorating patients. This session emphasises the importance of cognitive and social skills developed alongside practical skills in the simulated setting.

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The Family Model – A transgenerational approach to mental health in families This workshop will provide an overview on The Family Model (TFM) and its use in promoting and facilitating a trans­generational family focus in Mental Health services, over the past 10­ - 15 years. Each of the speakers will address a different perspective, including service user/consumer, clinical practice, education & training, research and policy. Adrian Falkov (chair) will provide an overview of TFM to set the scene and a ‘policy to practice’ perspective, based on use of TFM in Australia. Author: Heide Lloyd. The Family Model ­ A personal (consumer/patient) perspective | United Kingdom Heide will provide a description of her experiences as a child, adult, parent & grandparent, using TFM as the structure around which to ‘weave’ her story and demonstrate how TFM has assisted her in understanding the impact of symptoms on her & family and how she has used it in her management of symptoms and recovery (personal perspective). The Family Model ­ Education & training perspective ­ Marie Diggins | United Kingdom PhD Bente Weimand | Norway Authors: ­ Marie Diggins | United Kingdom PhD Bente Weimand | Norway This combined (UK & Norwegian) presentation will cover historical background to TFM and its use in eLearning (the Social Care Institute for Excellence)and a number of other UK initiatives, together with a description of the postgraduate masters course at the University Oslo/Akershus, using TFM. The Family Model ­ A research perspective PhD Anne Grant | Northern Ireland Author: PhD Anne Grant | Ireland Anne Grant will describe how she used TFM as the theoretical framework for her PhD looking at family focused (nursing) practice in Ireland. The Family Model ­ A service systems perspective ­ Mary Donaghy | Northern Ireland Authors: PhD Adrian Falkov | Australia ­ Mary Donaghy | N Ireland Mary Donaghy will discuss how TFM has been used to support & facilitate a cross service ‘whole of system’ change program in Belfast (NI) to achieve improved family focused practice. She will demonstrate its utility in achieving a broader approach to service design, delivery and evaluation.