Computational models that need to incorporate domain knowledge for realistic solutions to problems often lead to technologies that get transferred to developing countries. The support for managing the knowledge incorporated into these technologies is important for customisation to suit local conditions. This work investigates this problem through the challenge of incorporating food and nutrition therapy guidelines (FNTG) into ICT-based solution models for the meal planning problem (MPP) for HIV/AIDS patients in developing countries. An experiment is undertaken to demonstrate the limitations of existing approaches and framework is investigated for manageable incorporation of knowledge into solution models. The paper contributes a clear understanding of, and directions for addressing, the problem of support for managing the knowledge incorporated into solutions models to support customisability of technologies. The significance of this contribution is that solutions will allow resulting technologies to be customised for use in different global contexts.
Infrastructure sharing has been viewed as a plausible route to affordable ICT access in the wake of duplication of ICT infrastructure in developing countries. In spite of this belief in its effectiveness, getting ICT operators to share infrastructure can be inhibited by several challenges relating to regulatory approach, competition between players, and lack of consensus between regulators and business. This chapter uses evidence from Zimbabwe to assess how infrastructure sharing can be implemented in developing countries where coverage competition is yet to give way to service provision-based competition in the wake of disproportionate investment by network operators. It suggests that instead of push factors alone, infrastructure can best be shared when business' commercial interests and regulators' quest for affordable universal services coincide to form a win-win situation built on both push and pull factors.
This work investigates manageability challenges for knowledge incorporation in Genetic Algorithms (GAs) for solving the Meal Planning Problem (MPP). The MPP is an intractable problem with optimal solution models in literature leading to solutions that are hard to manage from the knowledge perspective. Manageable incorporation of knowledge into computational models for the MPP will help dietitians in nutrition-based disease therapy administration thereby improving the health of patients. An experimental study implementing a genetic model for the MPP was used to investigate the manageability challenges. The findings were that GAs do not have natural ways of supporting manageable incorporation of knowledge and knowledge incorporated into GAs using existing methods is hard to manage. Manageability is important because knowledge and models become easy to customize to suit different contexts. The novel contribution of this work is a new understanding on the matter of "manageability".
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