As potencialidades pedagógicas da WebQuest no ensino e aprendizagem da Geologia: um estudo com alunos do 11.º ano no tema "Principais etapas de formação das rochas sedimentares"

Relatório de estágio de mestrado em Ensino de Biologia e Geologia no 3.º Ciclo do Ensino Básico e no Ensino Secundário

Uma abordagem à organização e tratamento de dados baseada na resolução de problemas

Relatório de estágio de mestrado em Ensino do 1.º e 2.º Ciclo do Ensino Básico

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.

A aprendizagem baseada na resolução de problemas na aprendizagem da Geologia: uma intervenção centrada no tópico "Ocupação antrópica e problemas de ordenamento"

Dissertação de mestrado em Ensino de Biologia e Geologia no 3º Ciclo do Ensino Básico e no Ensino Secundário

Pensar, testar, opinar e construir: a resolução de problemas no jardim de infância e primeiro ciclo

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico

Desenvolvimento do pensamento computacional com recurso ao Scratch: uma experiência com alunos do 8ºano

Relatório de estágio de mestrado em Ensino de Informática

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

DNA evidence collecting in criminal investigation: Portuguese and Thai legal approaches

Doctoral Thesis in Juridical Sciences (Specialty in Public Legal Sciences)

Global vs. local nonlinear optimization techniques for human-like movement of an anthropomorphic robot

In this paper a comparison between using global and local optimization techniques for solving the problem of generating human-like arm and hand movements for an anthropomorphic dual arm robot is made. Although the objective function involved in each optimization problem is convex, there is no evidence that the admissible regions of these problems are convex sets. For the sequence of movements for which the numerical tests were done there were no significant differences between the optimal solutions obtained using the global and the local techniques. This suggests that the optimal solution obtained using the local solver is indeed a global solution.

Relatório de atividade profissional

Dissertação de mestrado em Ciências – Formação Contínua de Professores (área de especialização em Biologia e Geologia)

Emotional and behavioral problems in preschoolers: risk factors and assessment Issues

Tese de Doutoramento em Psicologia Aplicada.