Artificial neural networks (ANN) are very efficient in solving various kinds of problems But Lack of explanation capability (Black box nature of Neural Networks) is one of the most important reasons why artificial neural networks do not get necessary interest…

The number and scope of faculty and institutions involved in academic entrepreneurship continues to expand, and this has signifi cant implications for universities, involving potentially wonderful opportunities but also dire risks. This paper looks beyond academic capitalism, a theory that…

This article reviews the most significant milestones
in CAD methodologies for intelligent EM-based modeling and
design optimization using artificial neural networks and space
mapping. We consider knowledge-based and automatic neural
network model generation based on advanced data sampling
algorithms. Computationally…

Researchers, educators, policymakers, and other education stakeholders hope and anticipate that openness and open scholarship will generate positive outcomes for education and scholarship. Given the emerging nature of open practices, educators and scholars are finding themselves in a position in…

Our research project intends to build knowledge about HPC problems to be able to help local researchers. In order to advise users in choosing parallel machines to run their applications, we want to establish a general methodology, requiring as shallow…

This paper presents a knowledge-based approach to
reducing impediments to collaboration in a
distributed environment. A major impediment to
such collaboration is the issue of communications -
clearly and efficiently expressing the desires of every
stakeholder in the process, as…

Purpose – Information and communication technologies have became pervasive in people’s lives and in this changing world education cannot remain anchored in old-fashioned models which ignore the evolution through which society is going. This paper seeks to present the gamble…

This paper uses dynamic general equilibrium and computational methods, inspired by the multi-sector growth model structure in Stephen Turnovsky’s previous and more recent work, to develop a theory that unifies two of the traditional explanations of structural change: sector-biased technical…

No abstract.

Objective - The objective of this article is to demonstrate the efficacy of collaborative Evidence Based Information Practice (EBIP).

Methods - Application of theoretical frameworks of shared leadership, appreciative inquiry, and knowledge creation to propose an organisational effectiveness…