Strategic Partnerships in e-Health in Low and Lower Middle-Income Countries in Africa

Strategic partnerships are very important for the successful deployment of e-health as they play a crucial role in achieving common goals and creating an added value for the involved partners. In this paper, we will provide relevant information about strategic partnerships in e-health deployment in four African countries, namely Ethiopia, Ghana, Malawi, and Tunisia. A Partnership Assessment Tool is developed to analyze different aspects of partnerships and classify them. According to the analysis, 11 partnerships were strategic amongst the 15 identified. Findings analysis also shows that certain aspects, mainly sustainability, have to be enhanced to guarantee the impact of partnerships after the ending of its actions. Increased governmental support is required in addition to international funding resources to the successful deployment of e-health in the participating countries.publishedVersio

Robust optimization based energy management of a fuel cell/ ultra-capacitor hybrid electric vehicle under uncertainty

WOS:000531047600075This paper investigates the energy management of a fuel cell/ultra-capacitor hybrid electric vehicle (FCHEV) under uncertainty. In addition to fuel economy and fuel cell (FC) system slow dynamics, solutions' robustness is also considered as a key performance criterion. As previous studies focus on expected optimal performance under a deterministic framework and ignore possible data ambiguity, this paper considers uncertainties affecting power production, conversion and demand levels. Changing operation conditions, modeling and estimation claim several sources of errors. In practice, ignoring such uncertainties leads to high operation cost, poor overall system efficiency, performance failure and even infeasible solutions due to constraints violation. A robust optimization (RO) based energy management system (EMS) is studied in order to ensure optimal yet robust performance under uncertain parameters. The adopted RO based algorithm includes uncertainty in the cost function and constraints set and thus protects the system performance from feasibility and optimality issues. As RO approach is considered over conservative, conservatism level parameters are introduced to enable more flexible decision making and performance cost. Three different optimization case studies, namely classical deterministic, complete robust and variable conservatism level were investigated in order to assess the performance of the proposed approach. (C) 2020 Elsevier Ltd. All rights reserved