Socio-Emotional intelligence: A humanising approach to enhance wellbeing in higher education

Pages: 15-33

DOI: 10.1007/978-3-030-57430-7_2

Abstract:

Comparative network analysis provides an effective computational means to identify the similarities and differences between biological networks so that it helps transferring the prior knowledge across different biological networks. Since identifying the optimal biological network alignment is practically infeasible due to the computational complexity, a number of heuristic network alignment algorithms have been proposed. Among various heuristic approaches, comparative network analysis methods using random walk models are very effective to construct a reliable network alignment because it can accurately estimate the node correspondence by integrating node similarity and topological similarity. In this chapter, we introduce effective random walk models and their applications in developing comparative network analysis algorithms.

Source: Scopus

Socio-emotional intelligence: a humanising approach to enhance wellbeing in higher education

Authors: Devis-Rozental, C.

Publisher: Palgrave Macmillan

Abstract:

Devis-Rozental explores socio-emotional intelligence (SEI) within the context of higher education. She reviews the purpose of universities in the 21st century to assert the importance of SEI for personal and professional development and to find joy in what we do. Devis-Rozental includes a self-assessment questionnaire developed to allow the reader to reflect in their own SEI. Following this she explains the importance to challenge the them and us culture existing in areas of HE by developing research, teaching and working spaces that consider SEI and are therefore humanised. Only then, she argues, universities will set the tone as culture leaders, taking knowledge and practice to higher levels of meaning, and creating a deeper impact which in turn enriches society.

Source: Manual