The effectiveness of the Media Smart Program on promoting the critical thinking of children towards the use of celebrities in television advertising

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

The effects of land-use development policies on forest management

This paper develops a model of a forest owner operating in an open-city environment, where the rent for developed land is increasing concave in nearby preserved open space and is rising over time reflecting an upward trend in households’ income. Thus, our model creates the possibility of switching from forestry to residential use at some point in the future. In addition it allows the optimal harvest length to vary over time even if stumpage prices and regeneration costs remain constant. Within this framework we examine how adjacent preserved open space and alternative development constraints affect the private landowner´s decisions. We find that in the presence of rising income, preserved open space hastens regeneration and conversion cuts but leads to lower density development of nearby unzoned parcels due to indirect dynamic effects. We also find that both a binding development moratorium and a binding minimum-lot-size policy can postpone regeneration and conversion cut dates and thus help to protect open space even if only temporarily. However, the policies do not have the same effects on development density of converted forestland. While the former leads to high-density development, the latter encourages low-density development.

Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

A clustering approach for vehicle routing problems with hard time windows

Dissertação para obtenção do Grau de Mestre em Logica Computicional

Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

O uso da força no Direito Internacional = Use of force in Public International Law

Versão online da Revista Brasileira de Estudos Políticos, Belo Horizonte, nº 107, pp. 149-200, jul./dez.2013

Who uses NHS saúde 24 hotline? Has the user changed over time?

There has been an increase in the use of telephone-based services and internet throughout the years and, therefore, the Saúde 24 Hotline has become an important service in Portugal. This service aims to screen, counsel and refer the patient in order to avoid unnecessary visits to health institutions and also to indicate the most appropriate resource according to the illness. This work has two different questions: the first one examines the determinants of satisfaction that have more influence on the overall satisfaction of the Saúde 24 Hotline users. The second one aims to analyze if the confidence level of the users is increasing over time, measured by following the recommendation. The first study was conducted on a random sample collected from June to October 2014, which was taken from the User Satisfaction Survey. The second approach includes data from January 2008 to December 2014 from the Clinical Data Base of all users who have called the Hotline. Findings suggest that the majority of users are very satisfied with the service and the variables with more impact on the overall satisfaction are commitment and availability from the nurse, adequacy of call duration and quick identification of the problem. The survey indicates that 94% of respondents follow the recommendation and on average people have called the hotline 3 times in the previous year. The results from the Clinical Database show that people who were recommended to go to the emergency room are more likely to follow the advice than the people who were recommended to book routine appointments

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

The use of technology in Portuguese hospitals- The case of MRI

We study the determinants of MRI use across Portuguese NHS hospitals for patients belonging to specific DRGs. Using data on individual hospital admissions, we estimate a probit model including individual-, hospital-, time- and region-specific variables in order to explain the probability of a patient being sent for MRI. Results convey a tightening effect on the hospital’s budget constraint in the end of each year. Hospitals seem to account for regional characteristics when defining adoption patterns. Individual-specific variables are good predictors of MRI use. Measures taken by the Government only impact the short run. Finally, the gains from an MRI scan, as far as the probability of death is concerned, occur mainly for less severe patients.