2 resultados para Computational Intelligence in data-driven and hybrid Models and Data Analysis
Resumo:
Aim
A discussion of the concepts of leadership and emotional intelligence in nursing and midwifery education and practice.
Background
The need for emotionally intelligent leadership in the health professions is acknowledged internationally throughout the nursing and midwifery literature. The concepts of emotional intelligence and emotional-social intelligence have emerged as important factors for effective leadership in the healthcare professions and require further exploration and discussion. This paper will explore these concepts and discuss their importance in the healthcare setting with reference to current practices in the UK, Ireland and internationally.
Design
Discussion paper.
Data sources
A search of published evidence from 1990–2015 using key words (as outlined below) was undertaken from which relevant sources were selected to build an informed discussion.
Implications for nursing/midwifery
Fostering emotionally intelligent leadership in nursing and midwifery supports the provision of high quality and compassionate care. Globally, leadership has important implications for all stakeholders in the healthcare professions with responsibility for maintaining high standards of care. This includes all grades of nurses and midwives, students entering the professions, managerial staff, academics and policy makers.
Conclusion
This paper discusses the conceptual models of leadership and emotional intelligence and demonstrates an important link between the two. Further robust studies are required for ongoing evaluation of the different models of emotional intelligence and their link with effective leadership behaviour in the healthcare field internationally. This is of particular significance for professional undergraduate education to promote ongoing compassionate, safe and high quality standards of care.
Resumo:
This paper describes an implementation of a method capable of integrating parametric, feature based, CAD models based on commercial software (CATIA) with the SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities directly from the commercial CAD parameterisation is introduced, enabling the calculation of gradients with respect to CAD based design variables. To assess the accuracy and efficiency of the alternative approach, two aerodynamic optimisation problems are investigated: an inviscid, 3D, problem with multiple constraints, and a 2D high-lift aerofoil, viscous problem without any constraints. Initial results show the new parameterisation obtaining reliable optimums, with similar levels of performance of the software native parameterisations. In the final paper, details of computing CAD sensitivities will be provided, including accuracy as well as linking geometric sensitivities to aerodynamic objective functions and constraints; the impact in the robustness of the overall method will be assessed and alternative parameterisations will be included.