Abstract
Predictive modelling is a process used in predictive analytics to create a statistical model of future behaviour. Predictive analytics is the area of data mining concerned with forecasting probabilities and trends. On the other hand, Artificial Intelligence (AI) concerns itself with intelligent behaviour, i.e. the things that make us seem intelligent. Following this process of thinking, in this work the main goal is the assessment of the impact of using AI based tools for the development of intelligent predictive models, in particular those that may be used to establish the conditions in which the levels of manganese and turbidity in water supply are high. Indeed, one of the main problems that the water treatment plant at Monte Novo (in Evora, Portugal) uncovers is the appearance of high levels of manganese and turbidity in treated water, which sometimes exceed the parametric values established in Portuguese Law, respectively 50 mu g dm(-3) and 4 NTU. In this study we tried to find answers to the above problem by building predictive models. The models we developed shall enable the prediction of manganese and turbidity levels in treated water, in order to ensure that the water supply does not affect public health in a negative way and obeys the current legislation. The software used in this study was the Clementine 11.1. The C5.0 Algorithm was also used as a means of introducing Decision Trees and the K-Means Algorithm was used to construct clustering models. The data in the database was collected from 2005 to 2006 and includes reservoir water quality data, treated water data and volumes of water stored in the reservoir.

Abstract
MathIS is a new project that aims to reinvigorate secondary-school mathematics by exploiting insights of the dynamics of algorithmic problem solving. This paper describes the main ideas that underpin the project. In summary, we propose a central role for formal logic, the development of a calculational style of reasoning, the emphasis on the algorithmic nature of mathematics, and the promotion of self-discovery by the students. These ideas are discussed and the case is made, through a number of examples that show the teaching style that we want to introduce, for their relevance in shaping mathematics training for the years to come. In our opinion, the education of software engineers that work effectively with formal methods and mathematical abstractions should start before university and would benefit from the ideas discussed here.

Abstract
Throughout the modern world, healthcare is in a crisis. In response, health information systems are going through major changes: focusing more on the patient and what the patient can do to help to improve his own health care. A lot has been said about what the patient's role should be in the 21(st) century. However, in a way, the patient is still being left out, without the ability to decide about his role and impotent to exercise his rights as the owner of his own EHR. Moreover, there exists a general lack of awareness among the general public about the major risks involved in the unbounded disclosure of personal health related data. The continuous growth of privacy incidents, resulting from target profiling and mining off individual health histories, by human resource departments or insurance companies, demonstrates the fragile perception the general public has for these matters. To help us in assessing this situation we have conducted several interviews with patients older than 18 years in order to determine their opinion on matters regarding 'patient empowerment' and their associated EHRs: particularly who should have access and what were the real reasons behind those answers. In this paper we analyze the results of our questionnaire and present and discuss in detail the answers provided by 100 patients: 70 female and 30 male from diverse strata of the Portuguese population.

Abstract
The use of context is already a reality in different application fields. One such example is the Robotics field, where sensors are used to capture information about the surrounding environment, allowing the system to react to changes. But also in the multimedia cornmunications field, some work has recently emerged to allow combining sensed context and use that combined information to decide how to adapt the content. This paper describes the MULTICAO ontology, which lies at the core of an Adaptation Decision Engine, providing it with a formal description of the surrounding environment in a similar way as humans would describe it. This way the system has higher chances to take adaptation decisions that best meet users' expectations.

Abstract
In this paper it is presented a formulation for the DC Optimal Power Flow problem considering load and generation cost uncertainties and the corresponding solution algorithms. The paper also details the algorithms implemented to allow the integration of losses on the results as well the algorithm developed to compute the nodal marginal price in the presence of such uncertainties. Since loads and generation costs are represented by fuzzy numbers, nodal marginal prices are no longer represented by deterministic values, but instead, by membership functions. To illustrate the application of the proposed algorithms, this paper also includes results based on a small 3 bus system and on the IEEE 24 bus/38 branch test system.

Abstract