The role of temporary accommodation buildings for post-disaster housing reconstruction

The number of houses damaged or destroyed after disasters is frequently large, and re-housing of homeless people is one of the most important tasks of reconstruction programmes. Reconstruction works often last long and during that time, it is essential to provide victims with the minimum conditions to live with dignity, privacy, and protection. This research intends to demonstrate the crucial role of temporary accommodation buildings to provide spaces where people can live and gradually resume their life until they have a permanent house. The study also aims to identify the main problems of temporary accommodation strategies and to discuss some principles and guidelines in order to reach better design solutions. It is found that temporary accommodation is an issue that goes beyond the simple provision of buildings, since the whole space for temporary settlement is important. Likewise, temporary accommodation is a process that should start before a disaster occurs, as a preventive pre-planning. In spite of being temporary constructions, these housing buildings are one of the most important elements to provide in emergency scenarios, contributing for better recovery and reconstruction actions.

Non emergency patients transport - a mixed integer linear programming

This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.

The non-emergency patient transport modelled as a team orienteering problem

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

Genetic algorithms for the non emergency patients transport service

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.

HLT Hilotec: self-building manual for sustainable housing

The future of the construction industry will require changes at many levels. One is the ability of companies to adapt to new challenges, converting needs to opportunities and simultaneously contributing to the solving of social and environmental problems. In the coming decades we will see a change in attitude in the industry, with a strong tendency to adopt natural and recycled materials, as well as bet on green technology and social innovation oriented to emerging countries. On the other hand, emerging countries have a high demand for housing construction on a large scale, but the current techniques in the developed countries for building requires a large amount of natural resources and skilled labor. This contextualization brings sustainability problems for the construction sector in emerging countries, often with scarce natural resources and with the construction sector underdeveloped. Through a cooperative action between the construction company Mota-Engil Engineering and the University of Minho in Portugal, a construction technology was developed based on the use of Compressed Earth Blocks as part of a social concept for innovative small houses, favoring the adoption of local and natural materials and with the main premise of being dedicated to self-construction. The HiLoTec project - Development of a Sustainable Self-Construction System for Developing Countries was based on this idea. One of the several results of this project is this construction manual. To Mota-Engil the project was a platform for incubation of knowledge about earth construction and to obtain a constructive solution validated technically and scientifically, suitable to be implemented in the markets where it operates. For the University of Minho the project was an opportunity to strengthen skills in research, laboratory and scientific development, through the development of engineering studies, architecture and sustainability, as well as supporting the doctoral scholarships and dissemination of scientific publications. May the knowledge of this project be of benefit, in the future, for the welfare of those who build a HiLoTec house.

Consumption, wealth, stock and housing returns: evidence from emerging markets

We test the predictive ability of the transitory deviations of consumption from its common trend with aggregate wealth and labour income, cay, for both future equity and housing risk premia in emerging market economies. Using quarterly data for 31 markets, our country-level evidence shows that forecasting power of cay vis-à-vis stock returns is high for Brazil, China, Colombia, Israel, Korea, Latvia and Malaysia. As for housing returns, the empirical evidence suggests that financial and housing assets are perceived as complements in the case of Chile, Russia, South Africa and Thailand, and as substitutes in Argentina, Brazil, Hong Kong, Indonesia, Korea, Malaysia, Mexico and Taiwan. Using a panel econometric framework, we find that the cross-country heterogeneity observed in asset return predictability does not accrue to regional location, but can be attributed to differences in the degree of equity market development and in the level of income.

The housing evolution of Braga between late antiquity and the early meddle ages

The study of the domestic architecture evolution in Late Antiquity performs a fairly recent research subject within Hispanic historiography and represents one of the most significant results emerging from urban archaeology that has uncovered a relevant and innovative group of data related with the occupation of cities with Roman foundation between the fourth and eight centuries. In Braga the excavations conducted since 1976 identified remains of several domus that have been the object of systematic research studies in the past decade.2 In reality, the vast majority of the city Late Antiquity occupation continued to privilege areas where the previous domus of High Empire foundation were located. They were object of important reforms between the late third/early fourth centuries in a time when Bracara Augusta was elevated to capital of the new Callaecia province and endured an important urban renovation.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.