44 research outputs found

    Diagnosing and predicting wind turbine faults from SCADA data using support vector machines

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    Unscheduled or reactive maintenance on wind turbines due to component failure incurs significant downtime and, in turn, loss of revenue. To this end, it is important to be able to perform maintenance before it's needed. To date, a strong effort has been applied to developing Condition Monitoring Systems (CMSs) which rely on retrofitting expensive vibration or oil analysis sensors to the turbine. Instead, by performing complex analysis of existing data from the turbine's Supervisory Control and Data Acquisition (SCADA) system, valuable insights into turbine performance can be obtained at a much lower cost. In this paper, fault and alarm data from a turbine on the Southern coast of Ireland is analysed to identify periods of nominal and faulty operation. Classification techniques are then applied to detect and diagnose faults by taking into account other SCADA data such as temperature, pitch and rotor data. This is then extended to allow prediction and diagnosis in advance of specific faults. Results are provided which show recall scores generally above 80\% for fault detection and diagnosis, and prediction up to 24 hours in advance of specific faults, representing significant improvement over previous techniques

    Development and psychometric testing of the clinical leadership needs analysis (CLeeNA) instrument for nurses and midwives

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    Aim: The aim of this study is to report the development and psychometric testing of the clinical leadership needs analysis instrument (CLeeNA). Background: Limited emphasis is placed on the clinical leadership needs of nurses and midwives that are fundamental to supporting the delivery of high quality, safe patient care. Methods: A development and validation study of CLeeNA was undertaken using cross-sectional data. A sample of 324 registered nurses and midwives completed the questionnaire using a 7-point adjectival scale. Principal component analysis was conducted to explore scale grouping of items (n = 103 items). Results: Principal component analysis, item reduction and parallel analysis on the items of the instrument resulted in seven factors consisting of 56 items. These factors were identified as: Staff and Care Delivery; Technology and Care Initiatives; Self and Team Development; Standards of Care; Financial and Service Management; Leadership and Clinical Practice; Patient Safety and Risk Management. Conclusion: The identified factors are reflective of an ever-changing health care environment. Implications for Nursing Management: Potentially, after further testing, this instrument could be used by nursing management and educators to measure clinical leadership needs, inform the design of clinical leadership training programmes and provide valuable information about health care leadership development

    Conceptualising a model to guide nursing and midwifery in the community guided by an evidence review

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    Background: Successful models of nursing and midwifery in the community delivering healthcare throughout the lifespan and across a health and illness continuum are limited, yet necessary to guide global health services. Primary and community health services are the typical points of access for most people and the location where most care is delivered. The scope of primary healthcare is complex and multifaceted and therefore requires a practice framework with sound conceptual and theoretical underpinnings. The aim of this paper is to present a conceptual model informed by a scoping evidence review of the literature. Methods: A scoping evidence review of the literature was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Databases included CINAHL, MEDLINE, PsycINFO and SocINDEX using the EBSCO platform and the Cochrane Library using the keywords: model, nursing, midwifery, community, primary care. Grey literature for selected countries was searched using the Google ‘advanced’ search interface. Data extraction and quality appraisal for both empirical and grey literature were conducted independently by two reviewers. From 127 empirical and 24 non-empirical papers, data extraction parameters, in addition to the usual methodological features, included: the nature of nursing and midwifery; the population group; interventions and main outcomes; components of effective nursing and midwifery outcomes. Results: The evidence was categorised into six broad areas and subsequently synthesised into four themes. These were not mutually exclusive: (1) Integrated and Collaborative Care; (2) Organisation and Delivery of Nursing and Midwifery Care in the Community; (3) Adjuncts to Nursing Care and (4) Overarching Conceptual Model. It is the latter theme that is the focus of this paper. In essence, the model depicts a person/client on a lifespan and preventative-curative trajectory. The health related needs of the client, commensurate with their point position, relative to both trajectories, determines the nurse or midwife intervention. Consequently, it is this need, that determines the discipline or speciality of the nurse or midwife with the most appropriate competencies. Conclusion: Use of a conceptual model of nursing and midwifery to inform decision-making in primary/community based care ensures clinical outcomes are meaningful and more sustainable. Operationalising this model for nursing and midwifery in the community demands strong leadership and effective clinical governance

    Clinical and laboratory phenotypes in juvenile-onset Systemic Lupus Erythematosus across ethnicities in the UK.

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    Funder: LUPUS UKSystemic lupus erythematosus (SLE) is a systemic autoimmune/inflammatory disease. Patients diagnosed with juvenile-onset SLE (jSLE), when compared to individuals with adult-onset SLE, develop more severe organ involvement, increased disease activity and greater tissue and organ damage. In adult-onset SLE, clinical characteristics, pathomechanisms, disease progression and outcomes do not only vary between individuals and age groups, but also ethnicities. However, in children and young people, the influence of ethnicity on disease onset, phenotype and outcome has not been investigated in detail. In this study, we investigated clinical and laboratory characteristics in pediatric SLE patients from different ethnic backgrounds (White Caucasian, Asian, Black African/Caribbean) accessing data from a national cohort of jSLE patients (the UK JSLE Cohort Study). Among jSLE patients in the UK, ethnicity affects both the disease's clinical course and outcomes. At diagnosis, Black African/Caribbean jSLE patients show more "classical" laboratory and clinical features when compared to White Caucasian or Asian patients. Black African/Caribbean jSLE patients exhibit more renal involvement and more frequently receive cyclophosphamide and rituximab. Studies targeting ethnicity-specific contributors to disease expression and phenotypes are necessary to improve our pathophysiological understanding, diagnosis and treatment of jSLE

    Políticas e gestão da cultura : diálogos entre universidade e sociedade

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