Tourism demand modelling and forecasting with artificial neural network models: the Mozambique case study

This study is aimed to model and forecast the tourism demand for Mozambique for the period from January 2004 to December 2013 using artificial neural networks models. The number of overnight stays in Hotels was used as representative of the tourism demand. A set of independent variables were experimented in the input of the model, namely: Consumer Price Index, Gross Domestic Product and Exchange Rates, of the outbound tourism markets, South Africa, United State of America, Mozambique, Portugal and the United Kingdom. The best model achieved has 6.5% for Mean Absolute Percentage Error and 0.696 for Pearson correlation coefficient. A model like this with high accuracy of forecast is important for the economic agents to know the future growth of this activity sector, as it is important for stakeholders to provide products, services and infrastructures and for the hotels establishments to adequate its level of capacity to the tourism demand.

Knowledge about the rncci: an exploratory study about the perception of nursing students

The National Network of Continuing Care (RNCCI) was created in 2006 by Decree Law nr. 101/2006. Its mission is to supply adequate health and social care to all people who, independent of their age, are in a situation of dependence, and its action is articulated with the already existing health and social services, being a multidisciplinary team needed composed out of medical doctors, nurses, social workers and psychologists. Given the aforementioned it’s pertinent to perform research, with nurses and nursing students, about this new valence of care.