Design Drivers for Affordable and Sustainable Housing in Developing Countries

Current demand for housing worldwide has reached unprecedented levels due to factors such as human population growth, natural disasters and conflict. This is felt no more so than in developing countries which have experienced disproportionate levels of demand due to their innate vulnerability. Many current approaches to housing delivery in developing countries continue to utilize inappropriate construction methods and implementation procedures that are often problematic and unsustainable. As such affordability and sustainability are now vital considerations in the international development debate for housing the poor in developing countries in order to meet the long term sustainable development goals and needs of housing inhabitants. This paper utilized an extensive scoping study to examine the various facets impacting on design decision making relative to sustainable and affordable housing delivery in developing country contexts. Aspects of affordability, sustainability, design decision making, appropriate technology use, cultural awareness, as well as current barriers to affordable and sustainable construction in developing countries are examined in detail. Results highlighted the capability of indigenous knowledge, skills and materials as well as selected appropriate technology transfer and cultural awareness by foreign bodies can be utilized in innovative ways in addressing current housing needs in many developing country contexts.

Application of Fuzzy QFD to Aircraft Top Hierarchy Design

In this paper, based on the Quality Function Deployment ( QFD) method, theFuzzy Quality Function Deployment (FQFD) theory and the step-by-step hierarchy structure in aircrafttop decision design are studied. The fuzzy model for computing competitive factor in evaluation ispresented. The decision of key technologies for improving the performance and affordability of afixed-wing aircraft is studied using the model, and the result proves the feasibility of this model.

Multi-Agent Based Stochastic Dynamical Model to Measure Community Resilience

Emergency services and utilities need appropriate planning tools to analyze and improve infrastructure and community resilience to disasters.Recognized as a key metric of community resilience is the social well-being of a community during a disaster,which is made up of mental and physical social health.Other factors influencing community resilience directly or indirectly are emotional health,emergency services,and the availability of critical infrastructures services,such as food,agriculture,water,transportation,electric power,and communications system.It turns out that in computational social science literature dealing with community resilience,the role of these critical infrastructures along with some important social characteristics is not considered.To address these weaknesses,we develop a new multi-agent based stochastic dynamical model,standardized by overview,design concepts,details,and decision(ODD+D)protocol and derived from neuro-science,psychological and social sciences,to measure community resilience in terms of mental and physical well-being.Using this model,we analyze the micro-macro level dependence between the emergency services and power systems and social characteristics such as fear,risk perception,informationseeking behaviour,cooperation,flexibility,empathy,and experience,in an artificial society.Furthermore,we simulate this model in two case studies and show that a high level of flexibility,experience,and cooperation enhances community resilience.Implications for both theory and practice are discussed.